Overview

Dataset statistics

Number of variables87
Number of observations819592
Missing cells2923099
Missing cells (%)4.1%
Total size in memory550.3 MiB
Average record size in memory704.0 B

Variable types

Numeric74
Text13

Alerts

vlan_id has constant value ""Constant
bidirectional_cwr_packets has constant value ""Constant
bidirectional_ece_packets has constant value ""Constant
bidirectional_urg_packets has constant value ""Constant
src2dst_cwr_packets has constant value ""Constant
src2dst_ece_packets has constant value ""Constant
src2dst_urg_packets has constant value ""Constant
dst2src_cwr_packets has constant value ""Constant
dst2src_ece_packets has constant value ""Constant
dst2src_urg_packets has constant value ""Constant
requested_server_name has 85278 (10.4%) missing valuesMissing
client_fingerprint has 684924 (83.6%) missing valuesMissing
server_fingerprint has 685707 (83.7%) missing valuesMissing
user_agent has 729736 (89.0%) missing valuesMissing
content_type has 737454 (90.0%) missing valuesMissing
expiration_id is highly skewed (γ1 = 25.49637754)Skewed
tunnel_id is highly skewed (γ1 = 452.6541174)Skewed
bidirectional_packets is highly skewed (γ1 = 269.1751872)Skewed
bidirectional_bytes is highly skewed (γ1 = 288.7157973)Skewed
src2dst_packets is highly skewed (γ1 = 380.9165681)Skewed
src2dst_bytes is highly skewed (γ1 = 416.6942601)Skewed
dst2src_packets is highly skewed (γ1 = 277.3184197)Skewed
dst2src_bytes is highly skewed (γ1 = 341.911266)Skewed
bidirectional_min_piat_ms is highly skewed (γ1 = 23.12046912)Skewed
bidirectional_ack_packets is highly skewed (γ1 = 315.2545538)Skewed
bidirectional_psh_packets is highly skewed (γ1 = 271.5200403)Skewed
bidirectional_rst_packets is highly skewed (γ1 = 61.4520365)Skewed
src2dst_ack_packets is highly skewed (γ1 = 450.7065269)Skewed
src2dst_psh_packets is highly skewed (γ1 = 385.7670085)Skewed
src2dst_rst_packets is highly skewed (γ1 = 87.26733622)Skewed
dst2src_ack_packets is highly skewed (γ1 = 318.2594555)Skewed
dst2src_psh_packets is highly skewed (γ1 = 320.9870882)Skewed
dst2src_rst_packets is highly skewed (γ1 = 40.85727694)Skewed
expiration_id has 818337 (99.8%) zerosZeros
src_port has 18386 (2.2%) zerosZeros
dst_port has 18386 (2.2%) zerosZeros
vlan_id has 819592 (100.0%) zerosZeros
tunnel_id has 819588 (> 99.9%) zerosZeros
bidirectional_duration_ms has 21411 (2.6%) zerosZeros
src2dst_duration_ms has 500515 (61.1%) zerosZeros
dst2src_first_seen_ms has 30113 (3.7%) zerosZeros
dst2src_last_seen_ms has 30113 (3.7%) zerosZeros
dst2src_duration_ms has 491905 (60.0%) zerosZeros
dst2src_packets has 30113 (3.7%) zerosZeros
dst2src_bytes has 30113 (3.7%) zerosZeros
bidirectional_stddev_ps has 33969 (4.1%) zerosZeros
src2dst_stddev_ps has 529048 (64.6%) zerosZeros
dst2src_min_ps has 30113 (3.7%) zerosZeros
dst2src_mean_ps has 30113 (3.7%) zerosZeros
dst2src_stddev_ps has 479531 (58.5%) zerosZeros
dst2src_max_ps has 30113 (3.7%) zerosZeros
bidirectional_min_piat_ms has 317754 (38.8%) zerosZeros
bidirectional_mean_piat_ms has 21411 (2.6%) zerosZeros
bidirectional_stddev_piat_ms has 453887 (55.4%) zerosZeros
bidirectional_max_piat_ms has 21411 (2.6%) zerosZeros
src2dst_min_piat_ms has 617629 (75.4%) zerosZeros
src2dst_mean_piat_ms has 500515 (61.1%) zerosZeros
src2dst_stddev_piat_ms has 529796 (64.6%) zerosZeros
src2dst_max_piat_ms has 500515 (61.1%) zerosZeros
dst2src_min_piat_ms has 681861 (83.2%) zerosZeros
dst2src_mean_piat_ms has 491905 (60.0%) zerosZeros
dst2src_stddev_piat_ms has 554502 (67.7%) zerosZeros
dst2src_max_piat_ms has 491905 (60.0%) zerosZeros
bidirectional_syn_packets has 541039 (66.0%) zerosZeros
bidirectional_cwr_packets has 819592 (100.0%) zerosZeros
bidirectional_ece_packets has 819592 (100.0%) zerosZeros
bidirectional_urg_packets has 819592 (100.0%) zerosZeros
bidirectional_ack_packets has 539908 (65.9%) zerosZeros
bidirectional_psh_packets has 587663 (71.7%) zerosZeros
bidirectional_rst_packets has 760106 (92.7%) zerosZeros
bidirectional_fin_packets has 548638 (66.9%) zerosZeros
src2dst_syn_packets has 541041 (66.0%) zerosZeros
src2dst_cwr_packets has 819592 (100.0%) zerosZeros
src2dst_ece_packets has 819592 (100.0%) zerosZeros
src2dst_urg_packets has 819592 (100.0%) zerosZeros
src2dst_ack_packets has 542641 (66.2%) zerosZeros
src2dst_psh_packets has 589050 (71.9%) zerosZeros
src2dst_rst_packets has 770470 (94.0%) zerosZeros
src2dst_fin_packets has 553714 (67.6%) zerosZeros
dst2src_syn_packets has 548115 (66.9%) zerosZeros
dst2src_cwr_packets has 819592 (100.0%) zerosZeros
dst2src_ece_packets has 819592 (100.0%) zerosZeros
dst2src_urg_packets has 819592 (100.0%) zerosZeros
dst2src_ack_packets has 540142 (65.9%) zerosZeros
dst2src_psh_packets has 590102 (72.0%) zerosZeros
dst2src_rst_packets has 788785 (96.2%) zerosZeros
dst2src_fin_packets has 561665 (68.5%) zerosZeros
application_is_guessed has 768268 (93.7%) zerosZeros
label has 404571 (49.4%) zerosZeros

Reproduction

Analysis started2023-07-30 18:13:49.665257
Analysis finished2023-07-30 18:14:12.920314
Duration23.26 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

Distinct74530
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23575.71506
Minimum0
Maximum74529
Zeros35
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:13.744192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1251
Q17312
median18589
Q336424
95-th percentile62234
Maximum74529
Range74529
Interquartile range (IQR)29112

Descriptive statistics

Standard deviation19067.38412
Coefficient of variation (CV)0.8087722501
Kurtosis-0.4075938978
Mean23575.71506
Median Absolute Deviation (MAD)13160
Skewness0.7543258712
Sum1.932246746 × 1010
Variance363565137.1
MonotonicityNot monotonic
2023-07-30T15:14:14.322735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
< 0.1%
24 35
 
< 0.1%
26 35
 
< 0.1%
27 35
 
< 0.1%
28 35
 
< 0.1%
29 35
 
< 0.1%
30 35
 
< 0.1%
31 35
 
< 0.1%
32 35
 
< 0.1%
33 35
 
< 0.1%
Other values (74520) 819242
> 99.9%
ValueCountFrequency (%)
0 35
< 0.1%
1 35
< 0.1%
2 35
< 0.1%
3 35
< 0.1%
4 35
< 0.1%
ValueCountFrequency (%)
74529 2
< 0.1%
74528 2
< 0.1%
74527 2
< 0.1%
74526 2
< 0.1%
74525 2
< 0.1%

expiration_id
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001531249695
Minimum0
Maximum1
Zeros818337
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:14.569646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03910123828
Coefficient of variation (CV)25.53550763
Kurtosis648.0668491
Mean0.001531249695
Median Absolute Deviation (MAD)0
Skewness25.49637754
Sum1255
Variance0.001528906835
MonotonicityNot monotonic
2023-07-30T15:14:14.753405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 818337
99.8%
1 1255
 
0.2%
ValueCountFrequency (%)
0 818337
99.8%
1 1255
 
0.2%
ValueCountFrequency (%)
1 1255
 
0.2%
0 818337
99.8%

src_ip
Text

Distinct874
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:15.418888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length9
Mean length10.22869672
Min length2

Characters and Unicode

Total characters8383358
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st row192.168.1.111
2nd row192.168.1.111
3rd rowfe80::6529:a551:88b9:f0ca
4th row192.168.1.191
5th row192.168.1.191
ValueCountFrequency (%)
10.0.2.15 592433
72.3%
192.168.1.191 162496
 
19.8%
10.0.0.46 10192
 
1.2%
192.168.1.193 5514
 
0.7%
192.168.1.192 5200
 
0.6%
fe80::16cc:20ff:fe51:33ea 4363
 
0.5%
192.168.1.240 4200
 
0.5%
10.0.0.34 3574
 
0.4%
fe80::725a:fff:fee4:9bc0 3387
 
0.4%
192.168.1.249 2534
 
0.3%
Other values (864) 25699
 
3.1%
2023-07-30T15:14:16.132941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2417577
28.8%
1 2150020
25.6%
0 1261575
15.0%
2 831020
 
9.9%
5 612901
 
7.3%
9 382186
 
4.6%
6 218794
 
2.6%
8 218718
 
2.6%
: 68550
 
0.8%
f 57943
 
0.7%
Other values (8) 164074
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5761713
68.7%
Other Punctuation 2486127
29.7%
Lowercase Letter 135518
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2150020
37.3%
0 1261575
21.9%
2 831020
 
14.4%
5 612901
 
10.6%
9 382186
 
6.6%
6 218794
 
3.8%
8 218718
 
3.8%
4 37995
 
0.7%
3 36366
 
0.6%
7 12138
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
f 57943
42.8%
e 43305
32.0%
c 13319
 
9.8%
a 11703
 
8.6%
b 6319
 
4.7%
d 2929
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 2417577
97.2%
: 68550
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 8247840
98.4%
Latin 135518
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2417577
29.3%
1 2150020
26.1%
0 1261575
15.3%
2 831020
 
10.1%
5 612901
 
7.4%
9 382186
 
4.6%
6 218794
 
2.7%
8 218718
 
2.7%
: 68550
 
0.8%
4 37995
 
0.5%
Other values (2) 48504
 
0.6%
Latin
ValueCountFrequency (%)
f 57943
42.8%
e 43305
32.0%
c 13319
 
9.8%
a 11703
 
8.6%
b 6319
 
4.7%
d 2929
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8383358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2417577
28.8%
1 2150020
25.6%
0 1261575
15.0%
2 831020
 
9.9%
5 612901
 
7.3%
9 382186
 
4.6%
6 218794
 
2.6%
8 218718
 
2.6%
: 68550
 
0.8%
f 57943
 
0.7%
Other values (8) 164074
 
2.0%
Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:16.442600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters13933064
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2c:6e:85:56:dd:b7
2nd row2c:6e:85:56:dd:b7
3rd row2c:6e:85:56:dd:b7
4th row60:6c:66:cb:78:61
5th row60:6c:66:cb:78:61
ValueCountFrequency (%)
08:00:27:a3:83:43 593120
72.4%
60:6c:66:cb:78:61 162496
 
19.8%
78:e4:00:6c:39:cd 13766
 
1.7%
ec:1a:59:83:28:11 6831
 
0.8%
00:13:33:b0:18:50 6762
 
0.8%
00:62:6e:51:27:2e 5237
 
0.6%
14:cc:20:51:33:ea 4954
 
0.6%
70:5a:0f:e4:9b:c0 4220
 
0.5%
44:65:0d:56:cc:d3 4200
 
0.5%
00:16:6c:ab:6b:88 3483
 
0.4%
Other values (29) 14523
 
1.8%
2023-07-30T15:14:16.964304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 4097960
29.4%
0 2055447
14.8%
3 1847161
13.3%
8 1403988
 
10.1%
6 861451
 
6.2%
7 788594
 
5.7%
4 638590
 
4.6%
2 628637
 
4.5%
a 619195
 
4.4%
c 392454
 
2.8%
Other values (7) 599587
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8539606
61.3%
Other Punctuation 4097960
29.4%
Lowercase Letter 1295498
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2055447
24.1%
3 1847161
21.6%
8 1403988
16.4%
6 861451
10.1%
7 788594
 
9.2%
4 638590
 
7.5%
2 628637
 
7.4%
1 228927
 
2.7%
5 49802
 
0.6%
9 37009
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
a 619195
47.8%
c 392454
30.3%
b 185563
 
14.3%
e 54088
 
4.2%
d 28628
 
2.2%
f 15570
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 4097960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12637566
90.7%
Latin 1295498
 
9.3%

Most frequent character per script

Common
ValueCountFrequency (%)
: 4097960
32.4%
0 2055447
16.3%
3 1847161
14.6%
8 1403988
 
11.1%
6 861451
 
6.8%
7 788594
 
6.2%
4 638590
 
5.1%
2 628637
 
5.0%
1 228927
 
1.8%
5 49802
 
0.4%
Latin
ValueCountFrequency (%)
a 619195
47.8%
c 392454
30.3%
b 185563
 
14.3%
e 54088
 
4.2%
d 28628
 
2.2%
f 15570
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13933064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 4097960
29.4%
0 2055447
14.8%
3 1847161
13.3%
8 1403988
 
10.1%
6 861451
 
6.2%
7 788594
 
5.7%
4 638590
 
4.6%
2 628637
 
4.5%
a 619195
 
4.4%
c 392454
 
2.8%
Other values (7) 599587
 
4.3%
Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:17.244417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters6556736
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2c:6e:85
2nd row2c:6e:85
3rd row2c:6e:85
4th row60:6c:66
5th row60:6c:66
ValueCountFrequency (%)
08:00:27 593206
72.4%
60:6c:66 162496
 
19.8%
78:e4:00 13766
 
1.7%
ec:1a:59 9828
 
1.2%
00:13:33 6762
 
0.8%
00:62:6e 5237
 
0.6%
14:cc:20 4954
 
0.6%
70:5a:0f 4220
 
0.5%
44:65:0d 4200
 
0.5%
00:16:6c 3483
 
0.4%
Other values (24) 11440
 
1.4%
2023-07-30T15:14:18.105850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2031054
31.0%
: 1639184
25.0%
6 674645
 
10.3%
7 617037
 
9.4%
8 610386
 
9.3%
2 608136
 
9.3%
c 187733
 
2.9%
e 37634
 
0.6%
4 32010
 
0.5%
1 26572
 
0.4%
Other values (7) 92345
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4656349
71.0%
Other Punctuation 1639184
 
25.0%
Lowercase Letter 261203
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2031054
43.6%
6 674645
 
14.5%
7 617037
 
13.3%
8 610386
 
13.1%
2 608136
 
13.1%
4 32010
 
0.7%
1 26572
 
0.6%
5 23607
 
0.5%
3 22176
 
0.5%
9 10726
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
c 187733
71.9%
e 37634
 
14.4%
a 15464
 
5.9%
f 9291
 
3.6%
d 9015
 
3.5%
b 2066
 
0.8%
Other Punctuation
ValueCountFrequency (%)
: 1639184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6295533
96.0%
Latin 261203
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2031054
32.3%
: 1639184
26.0%
6 674645
 
10.7%
7 617037
 
9.8%
8 610386
 
9.7%
2 608136
 
9.7%
4 32010
 
0.5%
1 26572
 
0.4%
5 23607
 
0.4%
3 22176
 
0.4%
Latin
ValueCountFrequency (%)
c 187733
71.9%
e 37634
 
14.4%
a 15464
 
5.9%
f 9291
 
3.6%
d 9015
 
3.5%
b 2066
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6556736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2031054
31.0%
: 1639184
25.0%
6 674645
 
10.3%
7 617037
 
9.4%
8 610386
 
9.3%
2 608136
 
9.3%
c 187733
 
2.9%
e 37634
 
0.6%
4 32010
 
0.5%
1 26572
 
0.4%
Other values (7) 92345
 
1.4%

src_port
Real number (ℝ)

Distinct34168
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52145.2827
Minimum0
Maximum65535
Zeros18386
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:18.389322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33524
Q150243
median54774
Q359395
95-th percentile64130
Maximum65535
Range65535
Interquartile range (IQR)9152

Descriptive statistics

Standard deviation12818.44045
Coefficient of variation (CV)0.2458216695
Kurtosis7.966486338
Mean52145.2827
Median Absolute Deviation (MAD)4596
Skewness-2.664273881
Sum4.273785654 × 1010
Variance164312415.6
MonotonicityNot monotonic
2023-07-30T15:14:18.700144image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18386
 
2.2%
59370 4224
 
0.5%
80 2992
 
0.4%
53 1458
 
0.2%
443 1181
 
0.1%
546 596
 
0.1%
1900 593
 
0.1%
10001 591
 
0.1%
3080 568
 
0.1%
68 476
 
0.1%
Other values (34158) 788527
96.2%
ValueCountFrequency (%)
0 18386
2.2%
53 1458
 
0.2%
67 167
 
< 0.1%
68 476
 
0.1%
80 2992
 
0.4%
ValueCountFrequency (%)
65535 21
< 0.1%
65534 28
< 0.1%
65533 19
< 0.1%
65532 24
< 0.1%
65531 28
< 0.1%

dst_ip
Text

Distinct12207
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:19.460695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length14
Mean length13.47141749
Min length7

Characters and Unicode

Total characters11041066
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)< 0.1%

Sample

1st row239.255.255.250
2nd row224.0.0.251
3rd rowff02::fb
4th row192.168.33.254
5th row192.168.33.254
ValueCountFrequency (%)
192.168.33.254 463737
56.6%
208.91.112.53 25888
 
3.2%
8.8.8.8 9091
 
1.1%
23.51.123.27 6507
 
0.8%
192.168.1.191 5462
 
0.7%
192.168.1.1 4852
 
0.6%
239.255.255.250 3582
 
0.4%
192.168.1.223 3020
 
0.4%
93.184.220.29 2681
 
0.3%
172.217.23.238 2458
 
0.3%
Other values (12197) 292314
35.7%
2023-07-30T15:14:20.498601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2417577
21.9%
1 1746900
15.8%
2 1573378
14.3%
3 1216259
11.0%
5 761322
 
6.9%
8 709186
 
6.4%
9 700217
 
6.3%
4 697823
 
6.3%
6 653304
 
5.9%
0 253151
 
2.3%
Other values (8) 311949
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8525262
77.2%
Other Punctuation 2462081
 
22.3%
Lowercase Letter 53723
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1746900
20.5%
2 1573378
18.5%
3 1216259
14.3%
5 761322
8.9%
8 709186
8.3%
9 700217
8.2%
4 697823
 
8.2%
6 653304
 
7.7%
0 253151
 
3.0%
7 213722
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
f 43177
80.4%
e 3550
 
6.6%
c 2840
 
5.3%
b 2666
 
5.0%
a 1349
 
2.5%
d 141
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 2417577
98.2%
: 44504
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 10987343
99.5%
Latin 53723
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2417577
22.0%
1 1746900
15.9%
2 1573378
14.3%
3 1216259
11.1%
5 761322
 
6.9%
8 709186
 
6.5%
9 700217
 
6.4%
4 697823
 
6.4%
6 653304
 
5.9%
0 253151
 
2.3%
Other values (2) 258226
 
2.4%
Latin
ValueCountFrequency (%)
f 43177
80.4%
e 3550
 
6.6%
c 2840
 
5.3%
b 2666
 
5.0%
a 1349
 
2.5%
d 141
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11041066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2417577
21.9%
1 1746900
15.8%
2 1573378
14.3%
3 1216259
11.0%
5 761322
 
6.9%
8 709186
 
6.4%
9 700217
 
6.3%
4 697823
 
6.3%
6 653304
 
5.9%
0 253151
 
2.3%
Other values (8) 311949
 
2.8%
Distinct64
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:20.816082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters13933064
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row01:00:5e:7f:ff:fa
2nd row01:00:5e:00:00:fb
3rd row33:33:00:00:00:fb
4th row00:13:33:b0:18:50
5th row00:13:33:b0:18:50
ValueCountFrequency (%)
52:54:00:12:35:02 592253
72.3%
00:13:33:b0:18:50 162496
 
19.8%
14:cc:20:51:33:ea 16281
 
2.0%
38:72:c0:5e:6b:22 13762
 
1.7%
60:6c:66:cb:78:61 5462
 
0.7%
01:00:5e:7f:ff:fa 3582
 
0.4%
ec:1a:59:79:f4:89 3020
 
0.4%
ec:1a:59:83:28:11 1733
 
0.2%
33:33:00:00:00:02 1330
 
0.2%
33:33:00:01:00:03 1313
 
0.2%
Other values (54) 18360
 
2.2%
2023-07-30T15:14:21.297036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 4097960
29.4%
0 2551435
18.3%
5 1980963
14.2%
2 1843195
13.2%
3 1189929
 
8.5%
1 980124
 
7.0%
4 616717
 
4.4%
8 196830
 
1.4%
b 189492
 
1.4%
c 68771
 
0.5%
Other values (7) 217648
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9449741
67.8%
Other Punctuation 4097960
29.4%
Lowercase Letter 385363
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2551435
27.0%
5 1980963
21.0%
2 1843195
19.5%
3 1189929
12.6%
1 980124
 
10.4%
4 616717
 
6.5%
8 196830
 
2.1%
6 48498
 
0.5%
7 28184
 
0.3%
9 13866
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 189492
49.2%
c 68771
 
17.8%
f 51662
 
13.4%
e 46237
 
12.0%
a 27494
 
7.1%
d 1707
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 4097960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13547701
97.2%
Latin 385363
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
: 4097960
30.2%
0 2551435
18.8%
5 1980963
14.6%
2 1843195
13.6%
3 1189929
 
8.8%
1 980124
 
7.2%
4 616717
 
4.6%
8 196830
 
1.5%
6 48498
 
0.4%
7 28184
 
0.2%
Latin
ValueCountFrequency (%)
b 189492
49.2%
c 68771
 
17.8%
f 51662
 
13.4%
e 46237
 
12.0%
a 27494
 
7.1%
d 1707
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13933064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 4097960
29.4%
0 2551435
18.3%
5 1980963
14.2%
2 1843195
13.2%
3 1189929
 
8.5%
1 980124
 
7.0%
4 616717
 
4.4%
8 196830
 
1.4%
b 189492
 
1.4%
c 68771
 
0.5%
Other values (7) 217648
 
1.6%
Distinct30
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:21.566835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters6556736
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row01:00:5e
2nd row01:00:5e
3rd row33:33:00
4th row00:13:33
5th row00:13:33
ValueCountFrequency (%)
52:54:00 592253
72.3%
00:13:33 162496
 
19.8%
14:cc:20 16281
 
2.0%
38:72:c0 13762
 
1.7%
33:33:ff 7113
 
0.9%
33:33:00 6518
 
0.8%
01:00:5e 5689
 
0.7%
60:6c:66 5462
 
0.7%
ec:1a:59 4753
 
0.6%
00:16:6c 1311
 
0.2%
Other values (20) 3954
 
0.5%
2023-07-30T15:14:22.060500image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 1639184
25.0%
0 1581892
24.1%
5 1195367
18.2%
2 623177
 
9.5%
4 610115
 
9.3%
3 555847
 
8.5%
1 192164
 
2.9%
c 57951
 
0.9%
6 25607
 
0.4%
f 22865
 
0.3%
Other values (7) 52567
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4819510
73.5%
Other Punctuation 1639184
 
25.0%
Lowercase Letter 98042
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1581892
32.8%
5 1195367
24.8%
2 623177
 
12.9%
4 610115
 
12.7%
3 555847
 
11.5%
1 192164
 
4.0%
6 25607
 
0.5%
7 15474
 
0.3%
8 15074
 
0.3%
9 4793
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
c 57951
59.1%
f 22865
 
23.3%
e 12121
 
12.4%
a 4763
 
4.9%
d 255
 
0.3%
b 87
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 1639184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6458694
98.5%
Latin 98042
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
: 1639184
25.4%
0 1581892
24.5%
5 1195367
18.5%
2 623177
 
9.6%
4 610115
 
9.4%
3 555847
 
8.6%
1 192164
 
3.0%
6 25607
 
0.4%
7 15474
 
0.2%
8 15074
 
0.2%
Latin
ValueCountFrequency (%)
c 57951
59.1%
f 22865
 
23.3%
e 12121
 
12.4%
a 4763
 
4.9%
d 255
 
0.3%
b 87
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6556736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 1639184
25.0%
0 1581892
24.1%
5 1195367
18.2%
2 623177
 
9.5%
4 610115
 
9.3%
3 555847
 
8.5%
1 192164
 
2.9%
c 57951
 
0.9%
6 25607
 
0.4%
f 22865
 
0.3%
Other values (7) 52567
 
0.8%

dst_port
Real number (ℝ)

Distinct4068
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1081.609908
Minimum0
Maximum65502
Zeros18386
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:22.342867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53
Q153
median53
Q380
95-th percentile443
Maximum65502
Range65502
Interquartile range (IQR)27

Descriptive statistics

Standard deviation6550.765561
Coefficient of variation (CV)6.056495517
Kurtosis51.23445935
Mean1081.609908
Median Absolute Deviation (MAD)0
Skewness7.184910819
Sum886478828
Variance42912529.44
MonotonicityNot monotonic
2023-07-30T15:14:22.646095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 504014
61.5%
443 136900
 
16.7%
80 131070
 
16.0%
0 18386
 
2.2%
49153 3479
 
0.4%
123 3043
 
0.4%
1900 2371
 
0.3%
49152 1315
 
0.2%
3080 1274
 
0.2%
3478 974
 
0.1%
Other values (4058) 16766
 
2.0%
ValueCountFrequency (%)
0 18386
 
2.2%
7 2
 
< 0.1%
22 2
 
< 0.1%
53 504014
61.5%
67 476
 
0.1%
ValueCountFrequency (%)
65502 2
< 0.1%
65173 4
< 0.1%
65035 4
< 0.1%
64964 4
< 0.1%
64913 4
< 0.1%

protocol
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.77410956
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:22.875247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q16
median17
Q317
95-th percentile17
Maximum58
Range57
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.69272454
Coefficient of variation (CV)0.558491604
Kurtosis14.65896111
Mean13.77410956
Median Absolute Deviation (MAD)0
Skewness2.665111425
Sum11289150
Variance59.17801086
MonotonicityNot monotonic
2023-07-30T15:14:23.076151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
17 520282
63.5%
6 280924
34.3%
58 12934
 
1.6%
2 3188
 
0.4%
1 2264
 
0.3%
ValueCountFrequency (%)
1 2264
 
0.3%
2 3188
 
0.4%
6 280924
34.3%
17 520282
63.5%
58 12934
 
1.6%
ValueCountFrequency (%)
58 12934
 
1.6%
17 520282
63.5%
6 280924
34.3%
2 3188
 
0.4%
1 2264
 
0.3%

ip_version
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.033511796
Minimum4
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:23.298259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q14
median4
Q34
95-th percentile4
Maximum6
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2567111843
Coefficient of variation (CV)0.06364458499
Kurtosis54.69786013
Mean4.033511796
Median Absolute Deviation (MAD)0
Skewness7.529789284
Sum3305834
Variance0.06590063215
MonotonicityNot monotonic
2023-07-30T15:14:23.508601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
4 805859
98.3%
6 13733
 
1.7%
ValueCountFrequency (%)
4 805859
98.3%
6 13733
 
1.7%
ValueCountFrequency (%)
6 13733
 
1.7%
4 805859
98.3%

vlan_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:23.816791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:14:24.133999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

tunnel_id
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.464143135 × 10-5
Minimum0
Maximum3
Zeros819588
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:24.388414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.006627528443
Coefficient of variation (CV)452.6557743
Kurtosis204894.25
Mean1.464143135 × 10-5
Median Absolute Deviation (MAD)0
Skewness452.6541174
Sum12
Variance4.392413326 × 10-5
MonotonicityNot monotonic
2023-07-30T15:14:24.569568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 819588
> 99.9%
3 4
 
< 0.1%
ValueCountFrequency (%)
0 819588
> 99.9%
3 4
 
< 0.1%
ValueCountFrequency (%)
3 4
 
< 0.1%
0 819588
> 99.9%
Distinct403653
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.097594662 × 1011
Minimum7392
Maximum1.493732977 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:24.871790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile783443.7
Q13983149.5
median9016843
Q31.475171349 × 1012
95-th percentile1.493731402 × 1012
Maximum1.493732977 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)1.475167366 × 1012

Descriptive statistics

Standard deviation6.635485294 × 1011
Coefficient of variation (CV)1.619361075
Kurtosis-0.9928991105
Mean4.097594662 × 1011
Median Absolute Deviation (MAD)5872668
Skewness1.002685331
Sum3.358355804 × 1017
Variance4.402966509 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:25.244475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493730732 × 101256
 
< 0.1%
1.493730733 × 101256
 
< 0.1%
1.493729245 × 101254
 
< 0.1%
1.493731159 × 101252
 
< 0.1%
1.49373175 × 101252
 
< 0.1%
1.493730983 × 101248
 
< 0.1%
1.493730652 × 101246
 
< 0.1%
1.493729262 × 101246
 
< 0.1%
1.493731092 × 101246
 
< 0.1%
1.493729261 × 101244
 
< 0.1%
Other values (403643) 819092
99.9%
ValueCountFrequency (%)
7392 2
< 0.1%
8122 2
< 0.1%
13080 2
< 0.1%
13100 2
< 0.1%
13121 2
< 0.1%
ValueCountFrequency (%)
1.493732977 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732972 × 10122
< 0.1%
1.493732961 × 10122
< 0.1%
1.49373296 × 10122
< 0.1%
Distinct412505
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.097594889 × 1011
Minimum13099
Maximum1.49373298 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:25.592775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum13099
5-th percentile796671.6
Q14003233
median9042876
Q31.475171387 × 1012
95-th percentile1.493731409 × 1012
Maximum1.49373298 × 1012
Range1.493732967 × 1012
Interquartile range (IQR)1.475167384 × 1012

Descriptive statistics

Standard deviation6.635485305 × 1011
Coefficient of variation (CV)1.619360987
Kurtosis-0.9928991114
Mean4.097594889 × 1011
Median Absolute Deviation (MAD)5869331
Skewness1.002685331
Sum3.35835599 × 1017
Variance4.402966524 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:26.056109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493728105 × 101242
 
< 0.1%
1.493728071 × 101234
 
< 0.1%
1.493728087 × 101232
 
< 0.1%
1.493731028 × 101230
 
< 0.1%
1.493728072 × 101228
 
< 0.1%
1.493727927 × 101228
 
< 0.1%
1.38731541 × 101224
 
< 0.1%
1.493727961 × 101224
 
< 0.1%
1.493727927 × 101224
 
< 0.1%
1.493730472 × 101224
 
< 0.1%
Other values (412495) 819302
> 99.9%
ValueCountFrequency (%)
13099 2
< 0.1%
13119 2
< 0.1%
13139 2
< 0.1%
13158 2
< 0.1%
14160 2
< 0.1%
ValueCountFrequency (%)
1.49373298 × 10122
< 0.1%
1.493732979 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732969 × 10122
< 0.1%

bidirectional_duration_ms
Real number (ℝ)

Distinct62747
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22765.41256
Minimum0
Maximum1799999
Zeros21411
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:26.407904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q125
median59
Q35675
95-th percentile126748
Maximum1799999
Range1799999
Interquartile range (IQR)5650

Descriptive statistics

Standard deviation94382.05749
Coefficient of variation (CV)4.145853155
Kurtosis215.3482772
Mean22765.41256
Median Absolute Deviation (MAD)51
Skewness12.69607662
Sum1.865835001 × 1010
Variance8907972776
MonotonicityNot monotonic
2023-07-30T15:14:26.739688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21411
 
2.6%
25 12042
 
1.5%
24 12028
 
1.5%
23 11987
 
1.5%
26 11814
 
1.4%
27 11552
 
1.4%
28 11345
 
1.4%
22 11295
 
1.4%
21 11187
 
1.4%
29 11073
 
1.4%
Other values (62737) 693858
84.7%
ValueCountFrequency (%)
0 21411
2.6%
1 1140
 
0.1%
2 1079
 
0.1%
3 2273
 
0.3%
4 2438
 
0.3%
ValueCountFrequency (%)
1799999 6
< 0.1%
1799998 1
 
< 0.1%
1799997 1
 
< 0.1%
1799996 3
< 0.1%
1799995 3
< 0.1%

bidirectional_packets
Real number (ℝ)

Distinct1822
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.38092612
Minimum1
Maximum392213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:27.126191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q314
95-th percentile74
Maximum392213
Range392212
Interquartile range (IQR)12

Descriptive statistics

Standard deviation973.4780894
Coefficient of variation (CV)33.13299538
Kurtosis88594.95374
Mean29.38092612
Median Absolute Deviation (MAD)0
Skewness269.1751872
Sum24080372
Variance947659.5905
MonotonicityNot monotonic
2023-07-30T15:14:27.441864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 434142
53.0%
4 70758
 
8.6%
7 26293
 
3.2%
1 19487
 
2.4%
6 17782
 
2.2%
14 10374
 
1.3%
33 8974
 
1.1%
3 8738
 
1.1%
21 7249
 
0.9%
24 7166
 
0.9%
Other values (1812) 208629
25.5%
ValueCountFrequency (%)
1 19487
 
2.4%
2 434142
53.0%
3 8738
 
1.1%
4 70758
 
8.6%
5 4684
 
0.6%
ValueCountFrequency (%)
392213 2
< 0.1%
275466 2
< 0.1%
184518 4
< 0.1%
124890 4
< 0.1%
110611 4
< 0.1%

bidirectional_bytes
Real number (ℝ)

Distinct41366
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19180.81737
Minimum46
Maximum424668890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:27.793075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile168
Q1246
median408
Q32032
95-th percentile30692
Maximum424668890
Range424668844
Interquartile range (IQR)1786

Descriptive statistics

Standard deviation1007815.276
Coefficient of variation (CV)52.54287429
Kurtosis102689.9461
Mean19180.81737
Median Absolute Deviation (MAD)199
Skewness288.7157973
Sum1.572044447 × 1010
Variance1.01569163 × 1012
MonotonicityNot monotonic
2023-07-30T15:14:28.122246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
408 12849
 
1.6%
394 11999
 
1.5%
390 11883
 
1.4%
86 11507
 
1.4%
320 8685
 
1.1%
166 8300
 
1.0%
228 8219
 
1.0%
225 7908
 
1.0%
180 7350
 
0.9%
313 7318
 
0.9%
Other values (41356) 723574
88.3%
ValueCountFrequency (%)
46 2383
0.3%
54 12
 
< 0.1%
55 96
 
< 0.1%
60 544
 
0.1%
62 93
 
< 0.1%
ValueCountFrequency (%)
424668890 2
< 0.1%
307383769 2
< 0.1%
148005382 4
< 0.1%
128190733 4
< 0.1%
110825666 4
< 0.1%

src2dst_first_seen_ms
Real number (ℝ)

Distinct403653
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.097594662 × 1011
Minimum7392
Maximum1.493732977 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:28.410146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile783443.7
Q13983149.5
median9016843
Q31.475171349 × 1012
95-th percentile1.493731402 × 1012
Maximum1.493732977 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)1.475167366 × 1012

Descriptive statistics

Standard deviation6.635485294 × 1011
Coefficient of variation (CV)1.619361075
Kurtosis-0.9928991105
Mean4.097594662 × 1011
Median Absolute Deviation (MAD)5872668
Skewness1.002685331
Sum3.358355804 × 1017
Variance4.402966509 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:28.743674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493730732 × 101256
 
< 0.1%
1.493730733 × 101256
 
< 0.1%
1.493729245 × 101254
 
< 0.1%
1.493731159 × 101252
 
< 0.1%
1.49373175 × 101252
 
< 0.1%
1.493730983 × 101248
 
< 0.1%
1.493730652 × 101246
 
< 0.1%
1.493729262 × 101246
 
< 0.1%
1.493731092 × 101246
 
< 0.1%
1.493729261 × 101244
 
< 0.1%
Other values (403643) 819092
99.9%
ValueCountFrequency (%)
7392 2
< 0.1%
8122 2
< 0.1%
13080 2
< 0.1%
13100 2
< 0.1%
13121 2
< 0.1%
ValueCountFrequency (%)
1.493732977 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732972 × 10122
< 0.1%
1.493732961 × 10122
< 0.1%
1.49373296 × 10122
< 0.1%

src2dst_last_seen_ms
Real number (ℝ)

Distinct418495
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.097594888 × 1011
Minimum13080
Maximum1.49373298 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:29.087749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum13080
5-th percentile796636.15
Q14003194
median9042831
Q31.475171387 × 1012
95-th percentile1.493731409 × 1012
Maximum1.49373298 × 1012
Range1.493732967 × 1012
Interquartile range (IQR)1.475167384 × 1012

Descriptive statistics

Standard deviation6.635485305 × 1011
Coefficient of variation (CV)1.619360987
Kurtosis-0.9928991114
Mean4.097594888 × 1011
Median Absolute Deviation (MAD)5869318
Skewness1.002685331
Sum3.35835599 × 1017
Variance4.402966523 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:29.386722image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49372988 × 101248
 
< 0.1%
1.493728105 × 101246
 
< 0.1%
1.493727967 × 101240
 
< 0.1%
1.493728803 × 101236
 
< 0.1%
1.49373094 × 101234
 
< 0.1%
1.49373094 × 101234
 
< 0.1%
1.387315073 × 101232
 
< 0.1%
1.493730737 × 101232
 
< 0.1%
1.493731028 × 101230
 
< 0.1%
1.493728087 × 101230
 
< 0.1%
Other values (418485) 819230
> 99.9%
ValueCountFrequency (%)
13080 2
< 0.1%
13100 2
< 0.1%
13121 2
< 0.1%
13139 2
< 0.1%
14160 2
< 0.1%
ValueCountFrequency (%)
1.49373298 × 10122
< 0.1%
1.493732979 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732973 × 10122
< 0.1%
1.493732969 × 10122
< 0.1%

src2dst_duration_ms
Real number (ℝ)

Distinct62408
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22685.29405
Minimum0
Maximum1799999
Zeros500515
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:29.704715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35615
95-th percentile126745
Maximum1799999
Range1799999
Interquartile range (IQR)5615

Descriptive statistics

Standard deviation94376.74631
Coefficient of variation (CV)4.160261097
Kurtosis215.2969129
Mean22685.29405
Median Absolute Deviation (MAD)0
Skewness12.69404111
Sum1.859268552 × 1010
Variance8906970244
MonotonicityNot monotonic
2023-07-30T15:14:30.004642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 500515
61.1%
1 2413
 
0.3%
103 229
 
< 0.1%
206 228
 
< 0.1%
102 212
 
< 0.1%
19 197
 
< 0.1%
15 195
 
< 0.1%
2 194
 
< 0.1%
18 193
 
< 0.1%
17 186
 
< 0.1%
Other values (62398) 315030
38.4%
ValueCountFrequency (%)
0 500515
61.1%
1 2413
 
0.3%
2 194
 
< 0.1%
3 168
 
< 0.1%
4 128
 
< 0.1%
ValueCountFrequency (%)
1799999 6
< 0.1%
1799998 1
 
< 0.1%
1799997 1
 
< 0.1%
1799996 2
 
< 0.1%
1799995 2
 
< 0.1%

src2dst_packets
Real number (ℝ)

Distinct857
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.52411322
Minimum1
Maximum271835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:30.332491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q38
95-th percentile32
Maximum271835
Range271834
Interquartile range (IQR)7

Descriptive statistics

Standard deviation533.3452721
Coefficient of variation (CV)46.28080808
Kurtosis174595.8956
Mean11.52411322
Median Absolute Deviation (MAD)0
Skewness380.9165681
Sum9445071
Variance284457.1793
MonotonicityNot monotonic
2023-07-30T15:14:30.689787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 448900
54.8%
2 80477
 
9.8%
4 43500
 
5.3%
10 17544
 
2.1%
17 15793
 
1.9%
7 15039
 
1.8%
11 14240
 
1.7%
8 14061
 
1.7%
9 12251
 
1.5%
12 10926
 
1.3%
Other values (847) 146861
 
17.9%
ValueCountFrequency (%)
1 448900
54.8%
2 80477
 
9.8%
3 8802
 
1.1%
4 43500
 
5.3%
5 8082
 
1.0%
ValueCountFrequency (%)
271835 2
< 0.1%
97615 4
< 0.1%
91724 4
< 0.1%
42453 1
 
< 0.1%
37225 2
< 0.1%

src2dst_bytes
Real number (ℝ)

Distinct15247
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3633.795994
Minimum46
Maximum383809522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:31.003309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile72
Q180
median91
Q3938
95-th percentile4510
Maximum383809522
Range383809476
Interquartile range (IQR)858

Descriptive statistics

Standard deviation727001.4498
Coefficient of variation (CV)200.0666661
Kurtosis200235.7349
Mean3633.795994
Median Absolute Deviation (MAD)20
Skewness416.6942601
Sum2978230126
Variance5.28531108 × 1011
MonotonicityNot monotonic
2023-07-30T15:14:31.402136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 31617
 
3.9%
75 29786
 
3.6%
82 26315
 
3.2%
76 25846
 
3.2%
80 23921
 
2.9%
84 23834
 
2.9%
83 22788
 
2.8%
78 21052
 
2.6%
72 20217
 
2.5%
87 19338
 
2.4%
Other values (15237) 574878
70.1%
ValueCountFrequency (%)
46 2383
0.3%
54 27
 
< 0.1%
55 96
 
< 0.1%
60 544
 
0.1%
62 93
 
< 0.1%
ValueCountFrequency (%)
383809522 2
< 0.1%
146054307 4
< 0.1%
111505374 4
< 0.1%
51428692 1
 
< 0.1%
12644847 4
< 0.1%

dst2src_first_seen_ms
Real number (ℝ)

Distinct378929
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.595022058 × 1011
Minimum0
Maximum1.493732961 × 1012
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:31.710706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile283895
Q13327872
median8128794.5
Q318020410
95-th percentile1.493731384 × 1012
Maximum1.493732961 × 1012
Range1.493732961 × 1012
Interquartile range (IQR)14692538

Descriptive statistics

Standard deviation6.36483183 × 1011
Coefficient of variation (CV)1.770456962
Kurtosis-0.5430058818
Mean3.595022058 × 1011
Median Absolute Deviation (MAD)5447705
Skewness1.206398246
Sum2.946451319 × 1017
Variance4.051108422 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:31.999330image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30113
 
3.7%
9849460 28
 
< 0.1%
1.493728184 × 101226
 
< 0.1%
1.493730924 × 101224
 
< 0.1%
1.493729386 × 101224
 
< 0.1%
1.493729117 × 101224
 
< 0.1%
1.49373113 × 101224
 
< 0.1%
1.493729255 × 101222
 
< 0.1%
10348770 22
 
< 0.1%
1.493731485 × 101222
 
< 0.1%
Other values (378919) 789263
96.3%
ValueCountFrequency (%)
0 30113
3.7%
12401 2
 
< 0.1%
13099 2
 
< 0.1%
13119 2
 
< 0.1%
13139 2
 
< 0.1%
ValueCountFrequency (%)
1.493732961 × 10122
< 0.1%
1.49373296 × 10124
< 0.1%
1.49373296 × 10122
< 0.1%
1.49373296 × 10122
< 0.1%
1.49373296 × 10122
< 0.1%

dst2src_last_seen_ms
Real number (ℝ)

Distinct387079
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.595022272 × 1011
Minimum0
Maximum1.493732969 × 1012
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:32.333297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile297268
Q13345104.75
median8158774
Q318027355.5
95-th percentile1.493731392 × 1012
Maximum1.493732969 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)14682250.75

Descriptive statistics

Standard deviation6.364831841 × 1011
Coefficient of variation (CV)1.770456859
Kurtosis-0.5430058828
Mean3.595022272 × 1011
Median Absolute Deviation (MAD)5455164
Skewness1.206398246
Sum2.946451494 × 1017
Variance4.051108436 × 1023
MonotonicityNot monotonic
2023-07-30T15:14:32.725184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30113
 
3.7%
1.493731028 × 101230
 
< 0.1%
1.493730472 × 101224
 
< 0.1%
1.3873157 × 101220
 
< 0.1%
1.493731296 × 101220
 
< 0.1%
1.493727074 × 101218
 
< 0.1%
1.493731157 × 101218
 
< 0.1%
13569002 18
 
< 0.1%
1.493730925 × 101218
 
< 0.1%
1.493731049 × 101218
 
< 0.1%
Other values (387069) 789295
96.3%
ValueCountFrequency (%)
0 30113
3.7%
13099 2
 
< 0.1%
13119 2
 
< 0.1%
13139 2
 
< 0.1%
13158 2
 
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10122
< 0.1%
1.493732969 × 10122
< 0.1%
1.493732969 × 10124
< 0.1%
1.493732969 × 10122
< 0.1%
1.493732969 × 10122
< 0.1%

dst2src_duration_ms
Real number (ℝ)

Distinct60672
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21422.56733
Minimum0
Maximum1799978
Zeros491905
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:33.218918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35202
95-th percentile126058.45
Maximum1799978
Range1799978
Interquartile range (IQR)5202

Descriptive statistics

Standard deviation87325.32526
Coefficient of variation (CV)4.076323996
Kurtosis229.907688
Mean21422.56733
Median Absolute Deviation (MAD)0
Skewness12.80145442
Sum1.75577648 × 1010
Variance7625712433
MonotonicityNot monotonic
2023-07-30T15:14:33.535190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 491905
60.0%
1 11117
 
1.4%
2 3482
 
0.4%
3 2363
 
0.3%
4 1699
 
0.2%
5 1257
 
0.2%
6 1107
 
0.1%
9 1031
 
0.1%
8 1028
 
0.1%
10 1007
 
0.1%
Other values (60662) 303596
37.0%
ValueCountFrequency (%)
0 491905
60.0%
1 11117
 
1.4%
2 3482
 
0.4%
3 2363
 
0.3%
4 1699
 
0.2%
ValueCountFrequency (%)
1799978 1
< 0.1%
1799966 1
< 0.1%
1799918 1
< 0.1%
1799917 1
< 0.1%
1799884 1
< 0.1%

dst2src_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1524
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.8568129
Minimum0
Maximum238241
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:33.843108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q37
95-th percentile41
Maximum238241
Range238241
Interquartile range (IQR)6

Descriptive statistics

Standard deviation545.3978666
Coefficient of variation (CV)30.54284489
Kurtosis101524.4032
Mean17.8568129
Median Absolute Deviation (MAD)0
Skewness277.3184197
Sum14635301
Variance297458.8329
MonotonicityNot monotonic
2023-07-30T15:14:34.132391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 439471
53.6%
2 84743
 
10.3%
3 30972
 
3.8%
0 30113
 
3.7%
7 14986
 
1.8%
9 12871
 
1.6%
16 11773
 
1.4%
5 10753
 
1.3%
11 10557
 
1.3%
10 10509
 
1.3%
Other values (1514) 162844
 
19.9%
ValueCountFrequency (%)
0 30113
 
3.7%
1 439471
53.6%
2 84743
 
10.3%
3 30972
 
3.8%
4 8590
 
1.0%
ValueCountFrequency (%)
238241 2
< 0.1%
120378 2
< 0.1%
92794 4
< 0.1%
75240 2
< 0.1%
74533 4
< 0.1%

dst2src_bytes
Real number (ℝ)

SKEWED  ZEROS 

Distinct36740
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15547.02138
Minimum0
Maximum305372427
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:34.430418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile89
Q1153
median276
Q3950
95-th percentile24847
Maximum305372427
Range305372427
Interquartile range (IQR)797

Descriptive statistics

Standard deviation617817.1976
Coefficient of variation (CV)39.73862148
Kurtosis152969.1116
Mean15547.02138
Median Absolute Deviation (MAD)164
Skewness341.911266
Sum1.274221434 × 1010
Variance3.816980897 × 1011
MonotonicityNot monotonic
2023-07-30T15:14:34.771096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30113
 
3.7%
166 25315
 
3.1%
136 15661
 
1.9%
244 8804
 
1.1%
143 8434
 
1.0%
91 8264
 
1.0%
144 7883
 
1.0%
174 7406
 
0.9%
102 6557
 
0.8%
142 5466
 
0.7%
Other values (36730) 695689
84.9%
ValueCountFrequency (%)
0 30113
3.7%
54 756
 
0.1%
58 1505
 
0.2%
62 2
 
< 0.1%
66 297
 
< 0.1%
ValueCountFrequency (%)
305372427 2
< 0.1%
108240611 4
< 0.1%
107191507 2
< 0.1%
57515689 2
< 0.1%
48622876 2
< 0.1%

bidirectional_min_ps
Real number (ℝ)

Distinct319
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.21623686
Minimum43
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:35.123724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile54
Q166
median75
Q383
95-th percentile94
Maximum590
Range547
Interquartile range (IQR)17

Descriptive statistics

Standard deviation26.50962039
Coefficient of variation (CV)0.3524454492
Kurtosis93.16702801
Mean75.21623686
Median Absolute Deviation (MAD)9
Skewness7.90368431
Sum61646626
Variance702.7599732
MonotonicityNot monotonic
2023-07-30T15:14:35.474836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 196147
23.9%
66 84641
 
10.3%
75 36480
 
4.5%
86 34230
 
4.2%
76 32075
 
3.9%
80 29950
 
3.7%
82 29025
 
3.5%
84 27288
 
3.3%
78 26248
 
3.2%
83 25993
 
3.2%
Other values (309) 297515
36.3%
ValueCountFrequency (%)
43 48
 
< 0.1%
46 2513
 
0.3%
54 196147
23.9%
55 96
 
< 0.1%
56 2
 
< 0.1%
ValueCountFrequency (%)
590 23
< 0.1%
553 12
< 0.1%
551 2
 
< 0.1%
549 8
 
< 0.1%
548 2
 
< 0.1%

bidirectional_mean_ps
Real number (ℝ)

Distinct87070
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191.7299504
Minimum46
Maximum1350.138895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:35.790454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile68
Q1108.3333333
median155
Q3222.5
95-th percentile489.1406087
Maximum1350.138895
Range1304.138895
Interquartile range (IQR)114.1666667

Descriptive statistics

Standard deviation144.4414468
Coefficient of variation (CV)0.7533588073
Kurtosis9.739884295
Mean191.7299504
Median Absolute Deviation (MAD)53
Skewness2.792879231
Sum157140333.5
Variance20863.33154
MonotonicityNot monotonic
2023-07-30T15:14:36.153600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 16364
 
2.0%
68 12897
 
1.6%
56.28571429 11304
 
1.4%
55.71428571 11086
 
1.4%
90 9224
 
1.1%
160 8851
 
1.1%
83 8317
 
1.0%
114 8310
 
1.0%
112.5 8005
 
1.0%
156.5 7496
 
0.9%
Other values (87060) 717738
87.6%
ValueCountFrequency (%)
46 2513
0.3%
54 102
 
< 0.1%
54.5 96
 
< 0.1%
55 96
 
< 0.1%
55.03581267 4
 
< 0.1%
ValueCountFrequency (%)
1350.138895 2
< 0.1%
1307.40428 2
< 0.1%
1305.295718 2
< 0.1%
1301.207532 2
< 0.1%
1298.695546 2
< 0.1%

bidirectional_stddev_ps
Real number (ℝ)

Distinct110329
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.504112
Minimum0
Maximum728.1035406
Zeros33969
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:36.499563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.14718317
Q142.42640687
median113.137085
Q3239.3047856
95-th percentile615.7338601
Maximum728.1035406
Range728.1035406
Interquartile range (IQR)196.8783787

Descriptive statistics

Standard deviation185.2088331
Coefficient of variation (CV)1.049317385
Kurtosis0.7929051818
Mean176.504112
Median Absolute Deviation (MAD)84.14570696
Skewness1.329371362
Sum144661358.1
Variance34302.31188
MonotonicityNot monotonic
2023-07-30T15:14:36.889925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.3137085 51423
 
6.3%
0 33969
 
4.1%
43.13351365 15685
 
1.9%
19.79898987 14237
 
1.7%
3.346640106 12368
 
1.5%
4.535573676 11304
 
1.4%
3.14718317 11086
 
1.4%
98.28784258 10769
 
1.3%
187.383297 10419
 
1.3%
106.773124 9254
 
1.1%
Other values (110319) 639078
78.0%
ValueCountFrequency (%)
0 33969
4.1%
0.5006958946 80
 
< 0.1%
0.5007199428 4
 
< 0.1%
0.5007283325 4
 
< 0.1%
0.5007326011 2
 
< 0.1%
ValueCountFrequency (%)
728.1035406 2
< 0.1%
727.2549306 2
< 0.1%
723.849159 2
< 0.1%
723.6323307 2
< 0.1%
723.2549888 2
< 0.1%

bidirectional_max_ps
Real number (ℝ)

Distinct1456
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean503.5933879
Minimum46
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:37.353664image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile74
Q1143
median263
Q3571
95-th percentile1514
Maximum1514
Range1468
Interquartile range (IQR)428

Descriptive statistics

Standard deviation514.0466776
Coefficient of variation (CV)1.020757401
Kurtosis-0.2389283775
Mean503.5933879
Median Absolute Deviation (MAD)154
Skewness1.196956611
Sum412741112
Variance264243.9868
MonotonicityNot monotonic
2023-07-30T15:14:37.913947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1474 88193
 
10.8%
1514 60237
 
7.3%
74 21315
 
2.6%
62 14356
 
1.8%
86 13416
 
1.6%
66 12202
 
1.5%
143 11233
 
1.4%
571 9872
 
1.2%
244 9305
 
1.1%
91 8339
 
1.0%
Other values (1446) 571124
69.7%
ValueCountFrequency (%)
46 2513
 
0.3%
54 102
 
< 0.1%
55 192
 
< 0.1%
60 616
 
0.1%
62 14356
1.8%
ValueCountFrequency (%)
1514 60237
7.3%
1513 19
 
< 0.1%
1512 30
 
< 0.1%
1511 23
 
< 0.1%
1510 127
 
< 0.1%

src2dst_min_ps
Real number (ℝ)

Distinct324
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.38129948
Minimum43
Maximum994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:38.528644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile54
Q166
median75
Q383
95-th percentile94
Maximum994
Range951
Interquartile range (IQR)17

Descriptive statistics

Standard deviation26.5532221
Coefficient of variation (CV)0.3522521141
Kurtosis96.84654566
Mean75.38129948
Median Absolute Deviation (MAD)9
Skewness8.042966593
Sum61781910
Variance705.0736039
MonotonicityNot monotonic
2023-07-30T15:14:38.966367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 186646
22.8%
66 93168
 
11.4%
75 36480
 
4.5%
86 34239
 
4.2%
76 32073
 
3.9%
80 29952
 
3.7%
82 29025
 
3.5%
84 27284
 
3.3%
78 26236
 
3.2%
83 25991
 
3.2%
Other values (314) 298498
36.4%
ValueCountFrequency (%)
43 48
 
< 0.1%
46 2513
 
0.3%
54 186646
22.8%
55 192
 
< 0.1%
58 4
 
< 0.1%
ValueCountFrequency (%)
994 1
 
< 0.1%
590 40
< 0.1%
553 12
 
< 0.1%
551 2
 
< 0.1%
549 8
 
< 0.1%

src2dst_mean_ps
Real number (ℝ)

Distinct54590
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.5722873
Minimum46
Maximum1496.22811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:39.243642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile68
Q176
median83
Q394.4375
95-th percentile194.5
Maximum1496.22811
Range1450.22811
Interquartile range (IQR)18.4375

Descriptive statistics

Standard deviation67.50347395
Coefficient of variation (CV)0.671193584
Kurtosis80.60391972
Mean100.5722873
Median Absolute Deviation (MAD)8
Skewness6.984672621
Sum82428242.08
Variance4556.718995
MonotonicityNot monotonic
2023-07-30T15:14:39.670226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 35828
 
4.4%
86 34191
 
4.2%
76 31545
 
3.8%
80 29924
 
3.7%
82 28922
 
3.5%
84 27379
 
3.3%
78 25945
 
3.2%
83 25900
 
3.2%
72 24019
 
2.9%
77 23324
 
2.8%
Other values (54580) 532615
65.0%
ValueCountFrequency (%)
46 2513
0.3%
54 102
 
< 0.1%
54.03202149 2
 
< 0.1%
54.103558 2
 
< 0.1%
54.14763738 2
 
< 0.1%
ValueCountFrequency (%)
1496.22811 4
< 0.1%
1482.564644 2
< 0.1%
1480.155116 2
< 0.1%
1478.520593 2
< 0.1%
1476.822064 2
< 0.1%

src2dst_stddev_ps
Real number (ℝ)

Distinct81521
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.08094746
Minimum0
Maximum1023.890619
Zeros529048
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:40.069499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q368.77903215
95-th percentile287.5204341
Maximum1023.890619
Range1023.890619
Interquartile range (IQR)68.77903215

Descriptive statistics

Standard deviation112.5425332
Coefficient of variation (CV)2.120205809
Kurtosis9.418287121
Mean53.08094746
Median Absolute Deviation (MAD)0
Skewness2.908323753
Sum43504719.89
Variance12665.82178
MonotonicityNot monotonic
2023-07-30T15:14:40.364172image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 529048
64.6%
4 15730
 
1.9%
6 11307
 
1.4%
4 11088
 
1.4%
68.72824331 2527
 
0.3%
4.618802154 2020
 
0.2%
5.656854249 1886
 
0.2%
179.0171081 1606
 
0.2%
2.828427125 1359
 
0.2%
3.577708764 1245
 
0.2%
Other values (81511) 241776
29.5%
ValueCountFrequency (%)
0 529048
64.6%
0.4472135955 2
 
< 0.1%
0.5 8
 
< 0.1%
0.5 4
 
< 0.1%
0.5477225575 2
 
< 0.1%
ValueCountFrequency (%)
1023.890619 2
< 0.1%
1018.233765 2
< 0.1%
795.3082421 2
< 0.1%
784.4513157 2
< 0.1%
757.9997361 2
< 0.1%

src2dst_max_ps
Real number (ℝ)

Distinct1443
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.1281467
Minimum46
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:40.735284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile70
Q176
median84
Q3275
95-th percentile1038
Maximum1514
Range1468
Interquartile range (IQR)199

Descriptive statistics

Standard deviation334.7281451
Coefficient of variation (CV)1.359975077
Kurtosis5.596423829
Mean246.1281467
Median Absolute Deviation (MAD)10
Skewness2.428596799
Sum201724660
Variance112042.9312
MonotonicityNot monotonic
2023-07-30T15:14:41.046415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 43367
 
5.3%
75 35798
 
4.4%
86 34775
 
4.2%
76 31544
 
3.8%
80 29813
 
3.6%
82 29208
 
3.6%
84 27699
 
3.4%
83 26320
 
3.2%
78 25970
 
3.2%
1514 24840
 
3.0%
Other values (1433) 510258
62.3%
ValueCountFrequency (%)
46 2513
 
0.3%
54 102
 
< 0.1%
55 192
 
< 0.1%
60 616
 
0.1%
62 14374
1.8%
ValueCountFrequency (%)
1514 24840
3.0%
1513 17
 
< 0.1%
1512 24
 
< 0.1%
1511 30
 
< 0.1%
1510 76
 
< 0.1%

dst2src_min_ps
Real number (ℝ)

Distinct499
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.6377161
Minimum0
Maximum1224
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:41.351969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile54
Q154
median131
Q3227
95-th percentile408
Maximum1224
Range1224
Interquartile range (IQR)173

Descriptive statistics

Standard deviation118.497435
Coefficient of variation (CV)0.7565064017
Kurtosis0.8582540573
Mean156.6377161
Median Absolute Deviation (MAD)77
Skewness1.157023851
Sum128379019
Variance14041.64209
MonotonicityNot monotonic
2023-07-30T15:14:41.715802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 181065
 
22.1%
66 95254
 
11.6%
0 30113
 
3.7%
143 9494
 
1.2%
244 9362
 
1.1%
91 9359
 
1.1%
144 8289
 
1.0%
174 8203
 
1.0%
102 7071
 
0.9%
98 7005
 
0.9%
Other values (489) 454377
55.4%
ValueCountFrequency (%)
0 30113
 
3.7%
43 48
 
< 0.1%
54 181065
22.1%
56 2
 
< 0.1%
58 1511
 
0.2%
ValueCountFrequency (%)
1224 2
 
< 0.1%
701 4
 
< 0.1%
683 2
 
< 0.1%
565 2
 
< 0.1%
554 131
< 0.1%

dst2src_mean_ps
Real number (ℝ)

Distinct68897
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.1111455
Minimum0
Maximum1512.885002
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:42.106112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55.33333333
Q1121
median209
Q3337
95-th percentile725.907211
Maximum1512.885002
Range1512.885002
Interquartile range (IQR)216

Descriptive statistics

Standard deviation228.3223587
Coefficient of variation (CV)0.8612325909
Kurtosis6.454546931
Mean265.1111455
Median Absolute Deviation (MAD)102
Skewness2.260228354
Sum217282973.9
Variance52131.09948
MonotonicityNot monotonic
2023-07-30T15:14:42.602032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30113
 
3.7%
55.33333333 23795
 
2.9%
68 14048
 
1.7%
244 9039
 
1.1%
143 8574
 
1.0%
91 8341
 
1.0%
144 7974
 
1.0%
174 7548
 
0.9%
102 6868
 
0.8%
98 6846
 
0.8%
Other values (68887) 696446
85.0%
ValueCountFrequency (%)
0 30113
3.7%
54 872
 
0.1%
54.02197802 4
 
< 0.1%
54.02209945 12
 
< 0.1%
54.05548426 1
 
< 0.1%
ValueCountFrequency (%)
1512.885002 2
< 0.1%
1509.840695 2
< 0.1%
1509.772182 2
< 0.1%
1509.61316 2
< 0.1%
1507.84294 2
< 0.1%

dst2src_stddev_ps
Real number (ℝ)

Distinct85764
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.5128757
Minimum0
Maximum1023.890619
Zeros479531
Zeros (%)58.5%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:42.958658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3147.2247182
95-th percentile644.4987407
Maximum1023.890619
Range1023.890619
Interquartile range (IQR)147.2247182

Descriptive statistics

Standard deviation221.5194259
Coefficient of variation (CV)1.750963486
Kurtosis0.7481159085
Mean126.5128757
Median Absolute Deviation (MAD)0
Skewness1.541248203
Sum103688940.8
Variance49070.85604
MonotonicityNot monotonic
2023-07-30T15:14:43.373272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 479531
58.5%
2.309401077 23795
 
2.9%
2.828427125 14310
 
1.7%
8.485281374 11459
 
1.4%
657.8197394 2552
 
0.3%
66.46803743 2221
 
0.3%
72.12489168 1782
 
0.2%
2.309401077 1758
 
0.2%
16.97056275 1699
 
0.2%
195.1614716 1374
 
0.2%
Other values (85754) 279111
34.1%
ValueCountFrequency (%)
0 479531
58.5%
0.2964997267 4
 
< 0.1%
0.2973176585 12
 
< 0.1%
0.5 2
 
< 0.1%
0.5773502692 2
 
< 0.1%
ValueCountFrequency (%)
1023.890619 2
 
< 0.1%
833.7033845 2
 
< 0.1%
818.6851247 6
< 0.1%
813.2525233 2
 
< 0.1%
810.2320655 2
 
< 0.1%

dst2src_max_ps
Real number (ℝ)

Distinct1448
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean471.4322687
Minimum0
Maximum1514
Zeros30113
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:43.719615image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile58
Q1142
median247
Q3501
95-th percentile1506
Maximum1514
Range1514
Interquartile range (IQR)359

Descriptive statistics

Standard deviation504.8126253
Coefficient of variation (CV)1.070806262
Kurtosis0.0775290524
Mean471.4322687
Median Absolute Deviation (MAD)142
Skewness1.312481789
Sum386382116
Variance254835.7867
MonotonicityNot monotonic
2023-07-30T15:14:44.021120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1474 99473
 
12.1%
1514 40801
 
5.0%
0 30113
 
3.7%
58 26304
 
3.2%
70 18520
 
2.3%
244 9293
 
1.1%
143 8706
 
1.1%
91 8294
 
1.0%
144 8042
 
1.0%
174 7629
 
0.9%
Other values (1438) 562417
68.6%
ValueCountFrequency (%)
0 30113
3.7%
54 872
 
0.1%
58 26304
3.2%
60 6
 
< 0.1%
61 54
 
< 0.1%
ValueCountFrequency (%)
1514 40801
5.0%
1513 2
 
< 0.1%
1512 8
 
< 0.1%
1511 5
 
< 0.1%
1510 121
 
< 0.1%

bidirectional_min_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct2702
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean270.6698845
Minimum0
Maximum119989
Zeros317754
Zeros (%)38.8%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:44.370362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13
Q333
95-th percentile209
Maximum119989
Range119989
Interquartile range (IQR)33

Descriptive statistics

Standard deviation5003.798423
Coefficient of variation (CV)18.4867202
Kurtosis539.2649747
Mean270.6698845
Median Absolute Deviation (MAD)13
Skewness23.12046912
Sum221838872
Variance25037998.65
MonotonicityNot monotonic
2023-07-30T15:14:44.787646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 317754
38.8%
1 34043
 
4.2%
25 11789
 
1.4%
24 11696
 
1.4%
23 11595
 
1.4%
26 11465
 
1.4%
27 11277
 
1.4%
28 11060
 
1.3%
22 10962
 
1.3%
21 10795
 
1.3%
Other values (2692) 377156
46.0%
ValueCountFrequency (%)
0 317754
38.8%
1 34043
 
4.2%
2 6335
 
0.8%
3 1640
 
0.2%
4 924
 
0.1%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%
Distinct129375
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean924.0166869
Minimum0
Maximum119989
Zeros21411
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:45.242173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.600760456
Q123
median46
Q3388.9156872
95-th percentile3377.012162
Maximum119989
Range119989
Interquartile range (IQR)365.9156872

Descriptive statistics

Standard deviation5612.706797
Coefficient of variation (CV)6.074248308
Kurtosis338.3234782
Mean924.0166869
Median Absolute Deviation (MAD)36
Skewness17.0997827
Sum757316684.4
Variance31502477.59
MonotonicityNot monotonic
2023-07-30T15:14:45.775695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21411
 
2.6%
25 11727
 
1.4%
24 11582
 
1.4%
23 11474
 
1.4%
26 11337
 
1.4%
27 11116
 
1.4%
28 10926
 
1.3%
22 10869
 
1.3%
21 10745
 
1.3%
29 10602
 
1.3%
Other values (129365) 697803
85.1%
ValueCountFrequency (%)
0 21411
2.6%
0.2 2
 
< 0.1%
0.25 49
 
< 0.1%
0.3333333333 115
 
< 0.1%
0.4 4
 
< 0.1%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%
Distinct164362
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1335.500427
Minimum0
Maximum81606.48651
Zeros453887
Zeros (%)55.4%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:46.252896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3834.3064335
95-th percentile4816.034925
Maximum81606.48651
Range81606.48651
Interquartile range (IQR)834.3064335

Descriptive statistics

Standard deviation4616.975336
Coefficient of variation (CV)3.457112587
Kurtosis86.80526475
Mean1335.500427
Median Absolute Deviation (MAD)0
Skewness8.251637812
Sum1094565466
Variance21316461.25
MonotonicityNot monotonic
2023-07-30T15:14:46.775154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 453887
55.4%
1.527525232 1411
 
0.2%
1 1037
 
0.1%
1.732050808 939
 
0.1%
2.081665999 800
 
0.1%
2.309401077 675
 
0.1%
1.154700538 672
 
0.1%
2.886751346 524
 
0.1%
2.645751311 502
 
0.1%
3.464101615 488
 
0.1%
Other values (164352) 358657
43.8%
ValueCountFrequency (%)
0 453887
55.4%
0.3333333333 3
 
< 0.1%
0.4264014327 1
 
< 0.1%
0.4409585518 5
 
< 0.1%
0.4472135955 4
 
< 0.1%
ValueCountFrequency (%)
81606.48651 1
< 0.1%
80981.40412 2
< 0.1%
79552.34131 1
< 0.1%
79453.34636 1
< 0.1%
78082.97342 1
< 0.1%

bidirectional_max_piat_ms
Real number (ℝ)

Distinct25429
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4364.32586
Minimum0
Maximum119996
Zeros21411
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:47.294609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q124
median58
Q33866
95-th percentile10240
Maximum119996
Range119996
Interquartile range (IQR)3842

Descriptive statistics

Standard deviation13044.27116
Coefficient of variation (CV)2.988839875
Kurtosis30.94878749
Mean4364.32586
Median Absolute Deviation (MAD)50
Skewness5.238194518
Sum3576966560
Variance170153010
MonotonicityNot monotonic
2023-07-30T15:14:47.788317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21411
 
2.6%
25 12005
 
1.5%
24 11924
 
1.5%
23 11896
 
1.5%
26 11758
 
1.4%
27 11466
 
1.4%
28 11313
 
1.4%
22 11291
 
1.4%
21 11201
 
1.4%
29 10946
 
1.3%
Other values (25419) 694381
84.7%
ValueCountFrequency (%)
0 21411
2.6%
1 1266
 
0.2%
2 2298
 
0.3%
3 3186
 
0.4%
4 2539
 
0.3%
ValueCountFrequency (%)
119996 2
< 0.1%
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
< 0.1%
119985 1
< 0.1%

src2dst_min_piat_ms
Real number (ℝ)

Distinct7924
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean832.2219031
Minimum0
Maximum120189
Zeros617629
Zeros (%)75.4%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:48.133912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile160
Maximum120189
Range120189
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8201.114372
Coefficient of variation (CV)9.854480328
Kurtosis146.5015358
Mean832.2219031
Median Absolute Deviation (MAD)0
Skewness11.7796858
Sum682082414
Variance67258276.95
MonotonicityNot monotonic
2023-07-30T15:14:48.601727image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 617629
75.4%
1 47024
 
5.7%
2 19566
 
2.4%
3 11855
 
1.4%
4 6976
 
0.9%
5 4543
 
0.6%
10 4042
 
0.5%
9 3894
 
0.5%
11 3678
 
0.4%
8 3660
 
0.4%
Other values (7914) 96725
 
11.8%
ValueCountFrequency (%)
0 617629
75.4%
1 47024
 
5.7%
2 19566
 
2.4%
3 11855
 
1.4%
4 6976
 
0.9%
ValueCountFrequency (%)
120189 2
< 0.1%
120130 2
< 0.1%
120027 2
< 0.1%
119989 2
< 0.1%
119988 2
< 0.1%

src2dst_mean_piat_ms
Real number (ℝ)

Distinct114169
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1750.70356
Minimum0
Maximum120189
Zeros500515
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:49.068380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3735.1111111
95-th percentile6937.020833
Maximum120189
Range120189
Interquartile range (IQR)735.1111111

Descriptive statistics

Standard deviation8539.649527
Coefficient of variation (CV)4.877838671
Kurtosis121.3586873
Mean1750.70356
Median Absolute Deviation (MAD)0
Skewness10.40326301
Sum1434862632
Variance72925614.04
MonotonicityNot monotonic
2023-07-30T15:14:49.531379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 500515
61.1%
1 2362
 
0.3%
103 305
 
< 0.1%
102 284
 
< 0.1%
4 260
 
< 0.1%
104 254
 
< 0.1%
3 247
 
< 0.1%
2 243
 
< 0.1%
6 233
 
< 0.1%
5 231
 
< 0.1%
Other values (114159) 314658
38.4%
ValueCountFrequency (%)
0 500515
61.1%
0.25 49
 
< 0.1%
0.5 19
 
< 0.1%
0.75 1
 
< 0.1%
1 2362
 
0.3%
ValueCountFrequency (%)
120189 2
< 0.1%
120130 2
< 0.1%
120027 2
< 0.1%
119989 2
< 0.1%
119988 2
< 0.1%

src2dst_stddev_piat_ms
Real number (ℝ)

Distinct146628
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1307.71428
Minimum0
Maximum84221.36739
Zeros529796
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:50.005836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3826.8152324
95-th percentile4895.105845
Maximum84221.36739
Range84221.36739
Interquartile range (IQR)826.8152324

Descriptive statistics

Standard deviation3816.825866
Coefficient of variation (CV)2.918700151
Kurtosis81.71098272
Mean1307.71428
Median Absolute Deviation (MAD)0
Skewness7.231669027
Sum1071792162
Variance14568159.69
MonotonicityNot monotonic
2023-07-30T15:14:50.461978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 529796
64.6%
0.7071067812 583
 
0.1%
1.414213562 404
 
< 0.1%
2.121320344 222
 
< 0.1%
2.828427125 187
 
< 0.1%
4.242640687 152
 
< 0.1%
3.535533906 147
 
< 0.1%
4.949747468 124
 
< 0.1%
6.363961031 124
 
< 0.1%
5.656854249 122
 
< 0.1%
Other values (146618) 287731
35.1%
ValueCountFrequency (%)
0 529796
64.6%
0.3333333333 1
 
< 0.1%
0.4472135955 4
 
< 0.1%
0.5 12
 
< 0.1%
0.5 85
 
< 0.1%
ValueCountFrequency (%)
84221.36739 1
< 0.1%
84151.36382 2
< 0.1%
84030.44856 1
< 0.1%
83972.4658 2
< 0.1%
83682.55202 2
< 0.1%

src2dst_max_piat_ms
Real number (ℝ)

Distinct25850
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4355.625284
Minimum0
Maximum131048
Zeros500515
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:50.866063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33896
95-th percentile10500
Maximum131048
Range131048
Interquartile range (IQR)3896

Descriptive statistics

Standard deviation13089.20092
Coefficient of variation (CV)3.005125571
Kurtosis30.66941682
Mean4355.625284
Median Absolute Deviation (MAD)0
Skewness5.208016931
Sum3569835638
Variance171327180.7
MonotonicityNot monotonic
2023-07-30T15:14:51.177093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 500515
61.1%
1 2416
 
0.3%
10048 1595
 
0.2%
10101 1383
 
0.2%
10080 1382
 
0.2%
10100 1354
 
0.2%
10098 1318
 
0.2%
10112 1317
 
0.2%
10095 1290
 
0.2%
10094 1287
 
0.2%
Other values (25840) 305735
37.3%
ValueCountFrequency (%)
0 500515
61.1%
1 2416
 
0.3%
2 196
 
< 0.1%
3 187
 
< 0.1%
4 253
 
< 0.1%
ValueCountFrequency (%)
131048 2
< 0.1%
121741 2
< 0.1%
120824 2
< 0.1%
120189 2
< 0.1%
120130 2
< 0.1%

dst2src_min_piat_ms
Real number (ℝ)

Distinct8773
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean667.1300989
Minimum0
Maximum591145
Zeros681861
Zeros (%)83.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:51.481391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile149
Maximum591145
Range591145
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6759.057073
Coefficient of variation (CV)10.13154268
Kurtosis344.6516396
Mean667.1300989
Median Absolute Deviation (MAD)0
Skewness14.52566525
Sum546774492
Variance45684852.51
MonotonicityNot monotonic
2023-07-30T15:14:51.831542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 681861
83.2%
1 20098
 
2.5%
2 7662
 
0.9%
3 6678
 
0.8%
4 5636
 
0.7%
5 4512
 
0.6%
6 4146
 
0.5%
7 3779
 
0.5%
8 3413
 
0.4%
9 3198
 
0.4%
Other values (8763) 78609
 
9.6%
ValueCountFrequency (%)
0 681861
83.2%
1 20098
 
2.5%
2 7662
 
0.9%
3 6678
 
0.8%
4 5636
 
0.7%
ValueCountFrequency (%)
591145 1
< 0.1%
590885 1
< 0.1%
472686 1
< 0.1%
236338 1
< 0.1%
197140 1
< 0.1%

dst2src_mean_piat_ms
Real number (ℝ)

Distinct110572
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1508.229016
Minimum0
Maximum591145
Zeros491905
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:52.125741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3536.0842391
95-th percentile6641.972619
Maximum591145
Range591145
Interquartile range (IQR)536.0842391

Descriptive statistics

Standard deviation7311.091178
Coefficient of variation (CV)4.847467528
Kurtosis366.7951503
Mean1508.229016
Median Absolute Deviation (MAD)0
Skewness13.84196134
Sum1236132435
Variance53452054.22
MonotonicityNot monotonic
2023-07-30T15:14:52.428000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 491905
60.0%
1 11116
 
1.4%
2 3570
 
0.4%
3 2473
 
0.3%
4 1836
 
0.2%
5 1405
 
0.2%
6 1235
 
0.2%
7 1047
 
0.1%
8 1044
 
0.1%
9 1037
 
0.1%
Other values (110562) 302924
37.0%
ValueCountFrequency (%)
0 491905
60.0%
0.3333333333 1
 
< 0.1%
0.375 1
 
< 0.1%
0.5 4
 
< 0.1%
0.9601226994 2
 
< 0.1%
ValueCountFrequency (%)
591145 1
< 0.1%
590885 1
< 0.1%
499291.6667 1
< 0.1%
472691.3333 1
< 0.1%
472686 1
< 0.1%

dst2src_stddev_piat_ms
Real number (ℝ)

Distinct129120
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1208.900181
Minimum0
Maximum484430.9371
Zeros554502
Zeros (%)67.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:52.903787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3530.597462
95-th percentile4910.095779
Maximum484430.9371
Range484430.9371
Interquartile range (IQR)530.597462

Descriptive statistics

Standard deviation3791.124251
Coefficient of variation (CV)3.136010987
Kurtosis874.2722145
Mean1208.900181
Median Absolute Deviation (MAD)0
Skewness15.59942267
Sum990804917.4
Variance14372623.09
MonotonicityNot monotonic
2023-07-30T15:14:53.349845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 554502
67.7%
0.7071067812 319
 
< 0.1%
1.414213562 185
 
< 0.1%
2.121320344 105
 
< 0.1%
2.828427125 91
 
< 0.1%
4.242640687 81
 
< 0.1%
5.656854249 78
 
< 0.1%
3.535533906 75
 
< 0.1%
4.949747468 61
 
< 0.1%
1.5 58
 
< 0.1%
Other values (129110) 264037
32.2%
ValueCountFrequency (%)
0 554502
67.7%
0.3333333333 1
 
< 0.1%
0.4409585518 1
 
< 0.1%
0.4472135955 1
 
< 0.1%
0.5 11
 
< 0.1%
ValueCountFrequency (%)
484430.9371 1
< 0.1%
371016.5817 1
< 0.1%
306327.4519 1
< 0.1%
297417.4973 1
< 0.1%
279738.4932 1
< 0.1%

dst2src_max_piat_ms
Real number (ℝ)

Distinct24305
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4047.07849
Minimum0
Maximum985470
Zeros491905
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:53.752890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33230
95-th percentile10352
Maximum985470
Range985470
Interquartile range (IQR)3230

Descriptive statistics

Standard deviation12583.05834
Coefficient of variation (CV)3.109170819
Kurtosis253.0729751
Mean4047.07849
Median Absolute Deviation (MAD)0
Skewness8.784972947
Sum3316953154
Variance158333357.3
MonotonicityNot monotonic
2023-07-30T15:14:54.157445image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 491905
60.0%
1 11122
 
1.4%
2 3480
 
0.4%
3 2435
 
0.3%
4 1941
 
0.2%
10100 1528
 
0.2%
10101 1520
 
0.2%
10102 1489
 
0.2%
5 1477
 
0.2%
10097 1421
 
0.2%
Other values (24295) 301274
36.8%
ValueCountFrequency (%)
0 491905
60.0%
1 11122
 
1.4%
2 3480
 
0.4%
3 2435
 
0.3%
4 1941
 
0.2%
ValueCountFrequency (%)
985470 1
< 0.1%
866811 1
< 0.1%
749271 1
< 0.1%
748722 1
< 0.1%
748452 1
< 0.1%

bidirectional_syn_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6922371131
Minimum0
Maximum9
Zeros541039
Zeros (%)66.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:54.482913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9841958856
Coefficient of variation (CV)1.421761225
Kurtosis-0.412514195
Mean0.6922371131
Median Absolute Deviation (MAD)0
Skewness0.8778509957
Sum567352
Variance0.9686415412
MonotonicityNot monotonic
2023-07-30T15:14:54.935975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 541039
66.0%
2 261132
31.9%
3 10394
 
1.3%
1 5144
 
0.6%
4 1359
 
0.2%
7 204
 
< 0.1%
5 152
 
< 0.1%
6 104
 
< 0.1%
8 62
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
0 541039
66.0%
1 5144
 
0.6%
2 261132
31.9%
3 10394
 
1.3%
4 1359
 
0.2%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 62
 
< 0.1%
7 204
< 0.1%
6 104
< 0.1%
5 152
< 0.1%

bidirectional_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:55.147690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:14:55.336331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

bidirectional_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:55.535257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:14:55.711438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

bidirectional_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:55.895809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:14:56.333230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

bidirectional_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1808
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.2948223
Minimum0
Maximum392213
Zeros539908
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:56.630392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313
95-th percentile72
Maximum392213
Range392213
Interquartile range (IQR)13

Descriptive statistics

Standard deviation883.8632464
Coefficient of variation (CV)33.61358507
Kurtosis121110.033
Mean26.2948223
Median Absolute Deviation (MAD)0
Skewness315.2545538
Sum21551026
Variance781214.2383
MonotonicityNot monotonic
2023-07-30T15:14:56.982590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 539908
65.9%
6 26635
 
3.2%
5 14607
 
1.8%
13 11810
 
1.4%
32 8864
 
1.1%
20 7658
 
0.9%
21 6837
 
0.8%
11 6665
 
0.8%
15 6661
 
0.8%
9 6415
 
0.8%
Other values (1798) 183532
 
22.4%
ValueCountFrequency (%)
0 539908
65.9%
1 2679
 
0.3%
2 250
 
< 0.1%
3 1418
 
0.2%
4 1883
 
0.2%
ValueCountFrequency (%)
392213 2
< 0.1%
275465 2
< 0.1%
124890 4
< 0.1%
110611 4
< 0.1%
89524 2
< 0.1%

bidirectional_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct711
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.390011127
Minimum0
Maximum34903
Zeros587663
Zeros (%)71.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:57.364089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile18
Maximum34903
Range34903
Interquartile range (IQR)3

Descriptive statistics

Standard deviation89.52302982
Coefficient of variation (CV)16.60906215
Kurtosis95659.92259
Mean5.390011127
Median Absolute Deviation (MAD)0
Skewness271.5200403
Sum4417610
Variance8014.372868
MonotonicityNot monotonic
2023-07-30T15:14:57.751483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 587663
71.7%
2 23796
 
2.9%
6 21583
 
2.6%
7 20958
 
2.6%
3 19705
 
2.4%
5 18971
 
2.3%
8 16438
 
2.0%
4 16422
 
2.0%
9 12228
 
1.5%
10 9505
 
1.2%
Other values (701) 72323
 
8.8%
ValueCountFrequency (%)
0 587663
71.7%
1 2300
 
0.3%
2 23796
 
2.9%
3 19705
 
2.4%
4 16422
 
2.0%
ValueCountFrequency (%)
34903 2
< 0.1%
31175 2
< 0.1%
18767 1
< 0.1%
13249 1
< 0.1%
8200 2
< 0.1%

bidirectional_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct61
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18023724
Minimum0
Maximum259
Zeros760106
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:58.173341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum259
Range259
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.027162618
Coefficient of variation (CV)5.698947774
Kurtosis11238.10831
Mean0.18023724
Median Absolute Deviation (MAD)0
Skewness61.4520365
Sum147721
Variance1.055063043
MonotonicityNot monotonic
2023-07-30T15:14:58.578558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 760106
92.7%
3 29208
 
3.6%
1 20549
 
2.5%
2 5618
 
0.7%
4 2046
 
0.2%
5 1071
 
0.1%
9 175
 
< 0.1%
7 158
 
< 0.1%
6 135
 
< 0.1%
10 130
 
< 0.1%
Other values (51) 396
 
< 0.1%
ValueCountFrequency (%)
0 760106
92.7%
1 20549
 
2.5%
2 5618
 
0.7%
3 29208
 
3.6%
4 2046
 
0.2%
ValueCountFrequency (%)
259 2
< 0.1%
108 2
< 0.1%
93 2
< 0.1%
91 2
< 0.1%
89 2
< 0.1%

bidirectional_fin_packets
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6638327363
Minimum0
Maximum11
Zeros548638
Zeros (%)66.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:58.913619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9816022769
Coefficient of variation (CV)1.478689169
Kurtosis0.9746183928
Mean0.6638327363
Median Absolute Deviation (MAD)0
Skewness1.110677231
Sum544072
Variance0.96354303
MonotonicityNot monotonic
2023-07-30T15:14:59.178679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 548638
66.9%
2 242537
29.6%
1 16436
 
2.0%
3 7947
 
1.0%
4 2688
 
0.3%
5 805
 
0.1%
6 234
 
< 0.1%
9 132
 
< 0.1%
8 107
 
< 0.1%
7 62
 
< 0.1%
Other values (2) 6
 
< 0.1%
ValueCountFrequency (%)
0 548638
66.9%
1 16436
 
2.0%
2 242537
29.6%
3 7947
 
1.0%
4 2688
 
0.3%
ValueCountFrequency (%)
11 2
 
< 0.1%
10 4
 
< 0.1%
9 132
< 0.1%
8 107
< 0.1%
7 62
< 0.1%

src2dst_syn_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3542933557
Minimum0
Maximum7
Zeros541041
Zeros (%)66.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:14:59.499991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5224629246
Coefficient of variation (CV)1.474661933
Kurtosis8.887463037
Mean0.3542933557
Median Absolute Deviation (MAD)0
Skewness1.670581014
Sum290376
Variance0.2729675076
MonotonicityNot monotonic
2023-07-30T15:14:59.806461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 541041
66.0%
1 270049
32.9%
2 6555
 
0.8%
3 1461
 
0.2%
7 206
 
< 0.1%
5 112
 
< 0.1%
4 88
 
< 0.1%
6 80
 
< 0.1%
ValueCountFrequency (%)
0 541041
66.0%
1 270049
32.9%
2 6555
 
0.8%
3 1461
 
0.2%
4 88
 
< 0.1%
ValueCountFrequency (%)
7 206
 
< 0.1%
6 80
 
< 0.1%
5 112
 
< 0.1%
4 88
 
< 0.1%
3 1461
0.2%

src2dst_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:00.165054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:00.467481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

src2dst_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:00.875197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:01.187124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

src2dst_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:01.570946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:01.757857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

src2dst_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct847
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.670844762
Minimum0
Maximum271835
Zeros542641
Zeros (%)66.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:02.039629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile30
Maximum271835
Range271835
Interquartile range (IQR)6

Descriptive statistics

Standard deviation493.060322
Coefficient of variation (CV)50.98420398
Kurtosis233203.7644
Mean9.670844762
Median Absolute Deviation (MAD)0
Skewness450.7065269
Sum7926147
Variance243108.4811
MonotonicityNot monotonic
2023-07-30T15:15:02.416748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 542641
66.2%
3 41199
 
5.0%
6 18915
 
2.3%
9 18649
 
2.3%
16 15560
 
1.9%
7 13261
 
1.6%
8 12862
 
1.6%
10 12038
 
1.5%
11 9865
 
1.2%
5 8503
 
1.0%
Other values (837) 126099
 
15.4%
ValueCountFrequency (%)
0 542641
66.2%
1 537
 
0.1%
2 4111
 
0.5%
3 41199
 
5.0%
4 6042
 
0.7%
ValueCountFrequency (%)
271835 2
< 0.1%
97615 4
< 0.1%
42452 1
 
< 0.1%
37224 2
< 0.1%
36078 4
< 0.1%

src2dst_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct282
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.556729446
Minimum0
Maximum18766
Zeros589050
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:02.900385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum18766
Range18766
Interquartile range (IQR)1

Descriptive statistics

Standard deviation31.52807035
Coefficient of variation (CV)20.2527616
Kurtosis197215.1468
Mean1.556729446
Median Absolute Deviation (MAD)0
Skewness385.7670085
Sum1275883
Variance994.0192198
MonotonicityNot monotonic
2023-07-30T15:15:03.206516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 589050
71.9%
1 60157
 
7.3%
3 58602
 
7.2%
4 34460
 
4.2%
2 19265
 
2.4%
5 13653
 
1.7%
6 9356
 
1.1%
7 6815
 
0.8%
9 3965
 
0.5%
8 3691
 
0.5%
Other values (272) 20578
 
2.5%
ValueCountFrequency (%)
0 589050
71.9%
1 60157
 
7.3%
2 19265
 
2.4%
3 58602
 
7.2%
4 34460
 
4.2%
ValueCountFrequency (%)
18766 1
< 0.1%
13248 1
< 0.1%
6653 2
< 0.1%
3861 1
< 0.1%
3363 1
< 0.1%

src2dst_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct54
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1316569708
Minimum0
Maximum259
Zeros770470
Zeros (%)94.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:03.539244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum259
Range259
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8582994075
Coefficient of variation (CV)6.519209749
Kurtosis21487.95849
Mean0.1316569708
Median Absolute Deviation (MAD)0
Skewness87.26733622
Sum107905
Variance0.7366778729
MonotonicityNot monotonic
2023-07-30T15:15:03.858016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 770470
94.0%
2 21322
 
2.6%
1 14932
 
1.8%
3 9782
 
1.2%
4 1784
 
0.2%
5 519
 
0.1%
6 151
 
< 0.1%
10 136
 
< 0.1%
9 107
 
< 0.1%
7 68
 
< 0.1%
Other values (44) 321
 
< 0.1%
ValueCountFrequency (%)
0 770470
94.0%
1 14932
 
1.8%
2 21322
 
2.6%
3 9782
 
1.2%
4 1784
 
0.2%
ValueCountFrequency (%)
259 2
< 0.1%
108 2
< 0.1%
70 2
< 0.1%
55 2
< 0.1%
52 2
< 0.1%

src2dst_fin_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3269089986
Minimum0
Maximum10
Zeros553714
Zeros (%)67.6%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:04.119601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4775980439
Coefficient of variation (CV)1.460951047
Kurtosis3.200720823
Mean0.3269089986
Median Absolute Deviation (MAD)0
Skewness1.056678599
Sum267932
Variance0.2280998915
MonotonicityNot monotonic
2023-07-30T15:15:04.338309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 553714
67.6%
1 264282
32.2%
2 1424
 
0.2%
3 88
 
< 0.1%
8 26
 
< 0.1%
4 23
 
< 0.1%
5 14
 
< 0.1%
9 10
 
< 0.1%
6 5
 
< 0.1%
7 4
 
< 0.1%
ValueCountFrequency (%)
0 553714
67.6%
1 264282
32.2%
2 1424
 
0.2%
3 88
 
< 0.1%
4 23
 
< 0.1%
ValueCountFrequency (%)
10 2
 
< 0.1%
9 10
 
< 0.1%
8 26
< 0.1%
7 4
 
< 0.1%
6 5
 
< 0.1%

dst2src_syn_packets
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3379437574
Minimum0
Maximum6
Zeros548115
Zeros (%)66.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:04.549938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4880412658
Coefficient of variation (CV)1.444149374
Kurtosis-0.45039991
Mean0.3379437574
Median Absolute Deviation (MAD)0
Skewness0.9008296936
Sum276976
Variance0.2381842771
MonotonicityNot monotonic
2023-07-30T15:15:04.766845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 548115
66.9%
1 266359
32.5%
2 4763
 
0.6%
3 339
 
< 0.1%
4 10
 
< 0.1%
6 4
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
0 548115
66.9%
1 266359
32.5%
2 4763
 
0.6%
3 339
 
< 0.1%
4 10
 
< 0.1%
ValueCountFrequency (%)
6 4
 
< 0.1%
5 2
 
< 0.1%
4 10
 
< 0.1%
3 339
 
< 0.1%
2 4763
0.6%

dst2src_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:04.992225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:05.198122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

dst2src_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:05.422747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:05.623206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

dst2src_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros819592
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:05.809725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-07-30T15:15:06.002885image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%
ValueCountFrequency (%)
0 819592
100.0%

dst2src_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1524
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.62397754
Minimum0
Maximum238241
Zeros540142
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:06.238998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile41
Maximum238241
Range238241
Interquartile range (IQR)7

Descriptive statistics

Standard deviation505.43486
Coefficient of variation (CV)30.40396673
Kurtosis132109.5904
Mean16.62397754
Median Absolute Deviation (MAD)0
Skewness318.2594555
Sum13624879
Variance255464.3977
MonotonicityNot monotonic
2023-07-30T15:15:06.526034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 540142
65.9%
3 29088
 
3.5%
2 15861
 
1.9%
7 14755
 
1.8%
9 12753
 
1.6%
16 11793
 
1.4%
11 10437
 
1.3%
5 10392
 
1.3%
10 10171
 
1.2%
12 9823
 
1.2%
Other values (1514) 154377
 
18.8%
ValueCountFrequency (%)
0 540142
65.9%
1 3906
 
0.5%
2 15861
 
1.9%
3 29088
 
3.5%
4 6725
 
0.8%
ValueCountFrequency (%)
238241 2
< 0.1%
120378 2
< 0.1%
75240 2
< 0.1%
74533 4
< 0.1%
39095 2
< 0.1%

dst2src_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct618
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.833281682
Minimum0
Maximum34899
Zeros590102
Zeros (%)72.0%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:06.820043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile11
Maximum34899
Range34899
Interquartile range (IQR)1

Descriptive statistics

Standard deviation76.63220536
Coefficient of variation (CV)19.99127946
Kurtosis131280.7596
Mean3.833281682
Median Absolute Deviation (MAD)0
Skewness320.9870882
Sum3141727
Variance5872.494899
MonotonicityNot monotonic
2023-07-30T15:15:07.096619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 590102
72.0%
2 41862
 
5.1%
3 30771
 
3.8%
1 30720
 
3.7%
4 27779
 
3.4%
5 19033
 
2.3%
6 11980
 
1.5%
7 7713
 
0.9%
8 5845
 
0.7%
9 4830
 
0.6%
Other values (608) 48957
 
6.0%
ValueCountFrequency (%)
0 590102
72.0%
1 30720
 
3.7%
2 41862
 
5.1%
3 30771
 
3.8%
4 27779
 
3.4%
ValueCountFrequency (%)
34899 2
< 0.1%
24522 2
< 0.1%
8129 2
< 0.1%
7494 2
< 0.1%
5778 2
< 0.1%

dst2src_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct30
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04858026921
Minimum0
Maximum46
Zeros788785
Zeros (%)96.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:07.354083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3424832229
Coefficient of variation (CV)7.049842015
Kurtosis4012.745096
Mean0.04858026921
Median Absolute Deviation (MAD)0
Skewness40.85727694
Sum39816
Variance0.117294758
MonotonicityNot monotonic
2023-07-30T15:15:07.585989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 788785
96.2%
1 25261
 
3.1%
2 3971
 
0.5%
3 1085
 
0.1%
4 291
 
< 0.1%
5 68
 
< 0.1%
6 32
 
< 0.1%
7 12
 
< 0.1%
9 12
 
< 0.1%
17 8
 
< 0.1%
Other values (20) 67
 
< 0.1%
ValueCountFrequency (%)
0 788785
96.2%
1 25261
 
3.1%
2 3971
 
0.5%
3 1085
 
0.1%
4 291
 
< 0.1%
ValueCountFrequency (%)
46 2
< 0.1%
45 2
< 0.1%
44 2
< 0.1%
42 2
< 0.1%
36 2
< 0.1%

dst2src_fin_packets
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3369237377
Minimum0
Maximum8
Zeros561665
Zeros (%)68.5%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:07.801281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5424540331
Coefficient of variation (CV)1.610020228
Kurtosis13.11133457
Mean0.3369237377
Median Absolute Deviation (MAD)0
Skewness2.209375381
Sum276140
Variance0.294256378
MonotonicityNot monotonic
2023-07-30T15:15:08.010056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 561665
68.5%
1 246113
30.0%
2 7758
 
0.9%
3 2752
 
0.3%
4 835
 
0.1%
5 233
 
< 0.1%
8 136
 
< 0.1%
7 62
 
< 0.1%
6 38
 
< 0.1%
ValueCountFrequency (%)
0 561665
68.5%
1 246113
30.0%
2 7758
 
0.9%
3 2752
 
0.3%
4 835
 
0.1%
ValueCountFrequency (%)
8 136
 
< 0.1%
7 62
 
< 0.1%
6 38
 
< 0.1%
5 233
 
< 0.1%
4 835
0.1%
Distinct212
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:08.401940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length3
Mean length5.669639284
Min length3

Characters and Unicode

Total characters4646791
Distinct characters56
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowSSDP
2nd rowMDNS
3rd rowMDNS
4th rowDNS
5th rowDNS.Google
ValueCountFrequency (%)
dns 323427
39.5%
http 119979
 
14.6%
tls 106227
 
13.0%
dns.google 68771
 
8.4%
dns.facebook 37214
 
4.5%
dns.amazonaws 32051
 
3.9%
icmpv6 12934
 
1.6%
tls.google 9869
 
1.2%
http.ocsp 8515
 
1.0%
dns.twitter 7860
 
1.0%
Other values (202) 92745
 
11.3%
2023-07-30T15:15:09.118809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 712025
15.3%
N 513118
11.0%
D 511348
11.0%
T 445147
 
9.6%
o 348005
 
7.5%
. 233793
 
5.0%
e 187309
 
4.0%
P 180861
 
3.9%
L 142192
 
3.1%
H 140162
 
3.0%
Other values (46) 1232831
26.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3032962
65.3%
Lowercase Letter 1363050
29.3%
Other Punctuation 233793
 
5.0%
Decimal Number 16080
 
0.3%
Open Punctuation 313
 
< 0.1%
Close Punctuation 313
 
< 0.1%
Connector Punctuation 278
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 348005
25.5%
e 187309
13.7%
l 102140
 
7.5%
a 101786
 
7.5%
g 94138
 
6.9%
n 63302
 
4.6%
c 56418
 
4.1%
b 50445
 
3.7%
t 49801
 
3.7%
m 46055
 
3.4%
Other values (14) 263651
19.3%
Uppercase Letter
ValueCountFrequency (%)
S 712025
23.5%
N 513118
16.9%
D 511348
16.9%
T 445147
14.7%
P 180861
 
6.0%
L 142192
 
4.7%
H 140162
 
4.6%
G 96974
 
3.2%
A 84180
 
2.8%
F 39743
 
1.3%
Other values (12) 167212
 
5.5%
Decimal Number
ValueCountFrequency (%)
6 14027
87.2%
2 927
 
5.8%
3 491
 
3.1%
5 491
 
3.1%
1 144
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 233793
100.0%
Open Punctuation
ValueCountFrequency (%)
( 313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 313
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4396012
94.6%
Common 250779
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 712025
16.2%
N 513118
11.7%
D 511348
11.6%
T 445147
 
10.1%
o 348005
 
7.9%
e 187309
 
4.3%
P 180861
 
4.1%
L 142192
 
3.2%
H 140162
 
3.2%
l 102140
 
2.3%
Other values (36) 1113705
25.3%
Common
ValueCountFrequency (%)
. 233793
93.2%
6 14027
 
5.6%
2 927
 
0.4%
3 491
 
0.2%
5 491
 
0.2%
( 313
 
0.1%
) 313
 
0.1%
_ 278
 
0.1%
1 144
 
0.1%
- 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4646791
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 712025
15.3%
N 513118
11.0%
D 511348
11.0%
T 445147
 
9.6%
o 348005
 
7.5%
. 233793
 
5.0%
e 187309
 
4.0%
P 180861
 
3.9%
L 142192
 
3.1%
H 140162
 
3.0%
Other values (46) 1232831
26.5%
Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:09.432256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length14
Median length7
Mean length6.169580718
Min length3

Characters and Unicode

Total characters5056539
Distinct characters37
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowSystem
2nd rowNetwork
3rd rowNetwork
4th rowNetwork
5th rowNetwork
ValueCountFrequency (%)
network 535279
65.3%
web 220517
26.9%
advertisement 27667
 
3.4%
socialnetwork 8396
 
1.0%
system 7144
 
0.9%
cloud 5717
 
0.7%
download 5222
 
0.6%
media 3959
 
0.5%
unspecified 1474
 
0.2%
conncheck 648
 
0.1%
Other values (14) 3569
 
0.4%
2023-07-30T15:15:10.016357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 863489
17.1%
t 607763
12.0%
r 572672
11.3%
o 570498
11.3%
w 548901
10.9%
k 544323
10.8%
N 544303
10.8%
b 221095
 
4.4%
W 220517
 
4.4%
i 45280
 
0.9%
Other values (27) 317698
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4226257
83.6%
Uppercase Letter 830282
 
16.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 863489
20.4%
t 607763
14.4%
r 572672
13.6%
o 570498
13.5%
w 548901
13.0%
k 544323
12.9%
b 221095
 
5.2%
i 45280
 
1.1%
d 44264
 
1.0%
s 36773
 
0.9%
Other values (12) 171199
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
N 544303
65.6%
W 220517
26.6%
A 27680
 
3.3%
S 16487
 
2.0%
C 8014
 
1.0%
D 5223
 
0.6%
M 4261
 
0.5%
U 1478
 
0.2%
V 1035
 
0.1%
P 814
 
0.1%
Other values (5) 470
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 5056539
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 863489
17.1%
t 607763
12.0%
r 572672
11.3%
o 570498
11.3%
w 548901
10.9%
k 544323
10.8%
N 544303
10.8%
b 221095
 
4.4%
W 220517
 
4.4%
i 45280
 
0.9%
Other values (27) 317698
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5056539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 863489
17.1%
t 607763
12.0%
r 572672
11.3%
o 570498
11.3%
w 548901
10.9%
k 544323
10.8%
N 544303
10.8%
b 221095
 
4.4%
W 220517
 
4.4%
i 45280
 
0.9%
Other values (27) 317698
 
6.3%

application_is_guessed
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06262140187
Minimum0
Maximum1
Zeros768268
Zeros (%)93.7%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:10.232251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.242280898
Coefficient of variation (CV)3.868979147
Kurtosis11.03586083
Mean0.06262140187
Median Absolute Deviation (MAD)0
Skewness3.610517124
Sum51324
Variance0.05870003352
MonotonicityNot monotonic
2023-07-30T15:15:10.447547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 768268
93.7%
1 51324
 
6.3%
ValueCountFrequency (%)
0 768268
93.7%
1 51324
 
6.3%
ValueCountFrequency (%)
1 51324
 
6.3%
0 768268
93.7%

application_confidence
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.67962596
Minimum0
Maximum6
Zeros1474
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:10.658436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median6
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.224930636
Coefficient of variation (CV)0.2156710045
Kurtosis10.87041851
Mean5.67962596
Median Absolute Deviation (MAD)0
Skewness-3.580058881
Sum4654976
Variance1.500455064
MonotonicityNot monotonic
2023-07-30T15:15:10.851784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 766740
93.6%
1 50053
 
6.1%
0 1474
 
0.2%
3 871
 
0.1%
4 400
 
< 0.1%
5 54
 
< 0.1%
ValueCountFrequency (%)
0 1474
 
0.2%
1 50053
6.1%
3 871
 
0.1%
4 400
 
< 0.1%
5 54
 
< 0.1%
ValueCountFrequency (%)
6 766740
93.6%
5 54
 
< 0.1%
4 400
 
< 0.1%
3 871
 
0.1%
1 50053
 
6.1%
Distinct16272
Distinct (%)2.2%
Missing85278
Missing (%)10.4%
Memory size12.5 MiB
2023-07-30T15:15:11.318055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length79
Median length70
Mean length20.28968125
Min length3

Characters and Unicode

Total characters14898997
Distinct characters43
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique215 ?
Unique (%)< 0.1%

Sample

1st row239.255.255.250:1900
2nd row_googlecast._tcp.local
3rd row_googlecast._tcp.local
4th rowmobile.slashdot.org
5th rowaccounts.google.com
ValueCountFrequency (%)
www.facebook.com 8804
 
1.2%
e8218.dscb1.akamaiedge.net 8010
 
1.1%
star-mini.c10r.facebook.com 7997
 
1.1%
email.seznam.cz 7804
 
1.1%
www.google.com 5483
 
0.7%
detectportal.firefox.com 5246
 
0.7%
scontent.xx.fbcdn.net 4693
 
0.6%
d2tpbry8f62bv9.cloudfront.net 4480
 
0.6%
ib.adnxs.com 4066
 
0.6%
www.google-analytics.com 3858
 
0.5%
Other values (16260) 673882
91.8%
2023-07-30T15:15:12.127286image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1709880
 
11.5%
o 1187938
 
8.0%
e 1130631
 
7.6%
c 1113106
 
7.5%
a 977281
 
6.6%
t 842053
 
5.7%
m 803240
 
5.4%
s 729266
 
4.9%
n 686016
 
4.6%
i 597316
 
4.0%
Other values (33) 5122270
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12174542
81.7%
Other Punctuation 1712251
 
11.5%
Decimal Number 791978
 
5.3%
Dash Punctuation 220000
 
1.5%
Connector Punctuation 207
 
< 0.1%
Space Separator 9
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1187938
 
9.8%
e 1130631
 
9.3%
c 1113106
 
9.1%
a 977281
 
8.0%
t 842053
 
6.9%
m 803240
 
6.6%
s 729266
 
6.0%
n 686016
 
5.6%
i 597316
 
4.9%
d 546021
 
4.5%
Other values (16) 3561674
29.3%
Decimal Number
ValueCountFrequency (%)
1 179285
22.6%
2 120481
15.2%
0 86420
10.9%
8 67854
 
8.6%
3 67242
 
8.5%
9 57475
 
7.3%
5 57080
 
7.2%
6 54962
 
6.9%
7 50869
 
6.4%
4 50310
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 1709880
99.9%
: 2371
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 220000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 207
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12174542
81.7%
Common 2724455
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1187938
 
9.8%
e 1130631
 
9.3%
c 1113106
 
9.1%
a 977281
 
8.0%
t 842053
 
6.9%
m 803240
 
6.6%
s 729266
 
6.0%
n 686016
 
5.6%
i 597316
 
4.9%
d 546021
 
4.5%
Other values (16) 3561674
29.3%
Common
ValueCountFrequency (%)
. 1709880
62.8%
- 220000
 
8.1%
1 179285
 
6.6%
2 120481
 
4.4%
0 86420
 
3.2%
8 67854
 
2.5%
3 67242
 
2.5%
9 57475
 
2.1%
5 57080
 
2.1%
6 54962
 
2.0%
Other values (7) 103776
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14898997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1709880
 
11.5%
o 1187938
 
8.0%
e 1130631
 
7.6%
c 1113106
 
7.5%
a 977281
 
6.6%
t 842053
 
5.7%
m 803240
 
5.4%
s 729266
 
4.9%
n 686016
 
4.6%
i 597316
 
4.0%
Other values (33) 5122270
34.4%
Distinct47
Distinct (%)< 0.1%
Missing684924
Missing (%)83.6%
Memory size12.5 MiB
2023-07-30T15:15:12.467200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length47
Median length32
Mean length31.96772062
Min length5

Characters and Unicode

Total characters4305029
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st row07b4162d4db57554961824a21c4a0fde
2nd row07b4162d4db57554961824a21c4a0fde
3rd row07b4162d4db57554961824a21c4a0fde
4th row07b4162d4db57554961824a21c4a0fde
5th row07b4162d4db57554961824a21c4a0fde
ValueCountFrequency (%)
0ffee3ba8e615ad22535e7f771690a28 65649
48.7%
1a5fe5677b0e4fbbc854e8908225637d 23939
 
17.8%
07b4162d4db57554961824a21c4a0fde 20140
 
15.0%
dda6c525431b3259dac349220160cdcb 15252
 
11.3%
61d0d709fe7ac199ef4b2c52bc8cef75 6076
 
4.5%
6b87ab76e189e2222a12ff9d643060cd 2328
 
1.7%
c5ec106b91c503167f57054ca38da945 340
 
0.3%
dfa6e4a7819410092c24975e860e1380 124
 
0.1%
1,3,6,12,15,28,42 123
 
0.1%
bb32cf215dd58fdee6573e65933e6c55 107
 
0.1%
Other values (37) 590
 
0.4%
2023-07-30T15:15:13.028011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 414766
 
9.6%
2 391718
 
9.1%
e 378970
 
8.8%
7 334009
 
7.8%
a 304307
 
7.1%
f 289233
 
6.7%
0 268968
 
6.2%
6 267899
 
6.2%
1 266161
 
6.2%
8 235651
 
5.5%
Other values (7) 1153347
26.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2740476
63.7%
Lowercase Letter 1562484
36.3%
Other Punctuation 2069
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 414766
15.1%
2 391718
14.3%
7 334009
12.2%
0 268968
9.8%
6 267899
9.8%
1 266161
9.7%
8 235651
8.6%
3 206003
7.5%
4 190128
6.9%
9 165173
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 378970
24.3%
a 304307
19.5%
f 289233
18.5%
d 229305
14.7%
b 226530
14.5%
c 134139
 
8.6%
Other Punctuation
ValueCountFrequency (%)
, 2069
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2742545
63.7%
Latin 1562484
36.3%

Most frequent character per script

Common
ValueCountFrequency (%)
5 414766
15.1%
2 391718
14.3%
7 334009
12.2%
0 268968
9.8%
6 267899
9.8%
1 266161
9.7%
8 235651
8.6%
3 206003
7.5%
4 190128
6.9%
9 165173
 
6.0%
Latin
ValueCountFrequency (%)
e 378970
24.3%
a 304307
19.5%
f 289233
18.5%
d 229305
14.7%
b 226530
14.5%
c 134139
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4305029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 414766
 
9.6%
2 391718
 
9.1%
e 378970
 
8.8%
7 334009
 
7.8%
a 304307
 
7.1%
f 289233
 
6.7%
0 268968
 
6.2%
6 267899
 
6.2%
1 266161
 
6.2%
8 235651
 
5.5%
Other values (7) 1153347
26.8%
Distinct267
Distinct (%)0.2%
Missing685707
Missing (%)83.7%
Memory size12.5 MiB
2023-07-30T15:15:13.500018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters4284320
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row303951d4c50efb2e991652225a6f02b1
2nd row76cc3e2d3028143b23ec18e27dbd7ca9
3rd row303951d4c50efb2e991652225a6f02b1
4th row76cc3e2d3028143b23ec18e27dbd7ca9
5th rowb898351eb5e266aefd3723d466935494
ValueCountFrequency (%)
303951d4c50efb2e991652225a6f02b1 17183
 
12.8%
76cc3e2d3028143b23ec18e27dbd7ca9 9550
 
7.1%
2b33c1374db4ddf06942f92373c0b54b 5980
 
4.5%
fbe78c619e7ea20046131294ad087f05 5349
 
4.0%
410b9bedaf65dd26c6fe547154d60db4 5125
 
3.8%
7bee5c1d424b7e5f943b06983bb11422 4615
 
3.4%
d199ba0af2b08e204c73d6d81a1fd260 4279
 
3.2%
8d2a028aa94425f76ced7826b1f39039 4227
 
3.2%
ab41313cfec25328b20865eb1388e0a2 4047
 
3.0%
b898351eb5e266aefd3723d466935494 3851
 
2.9%
Other values (257) 69679
52.0%
2023-07-30T15:15:14.232598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 363206
 
8.5%
1 316234
 
7.4%
3 287941
 
6.7%
b 287500
 
6.7%
5 284175
 
6.6%
0 278494
 
6.5%
e 276077
 
6.4%
d 274180
 
6.4%
9 272434
 
6.4%
4 257200
 
6.0%
Other values (6) 1386879
32.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2754860
64.3%
Lowercase Letter 1529460
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 363206
13.2%
1 316234
11.5%
3 287941
10.5%
5 284175
10.3%
0 278494
10.1%
9 272434
9.9%
4 257200
9.3%
6 249631
9.1%
7 228820
8.3%
8 216725
7.9%
Lowercase Letter
ValueCountFrequency (%)
b 287500
18.8%
e 276077
18.1%
d 274180
17.9%
f 240722
15.7%
c 232602
15.2%
a 218379
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2754860
64.3%
Latin 1529460
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 363206
13.2%
1 316234
11.5%
3 287941
10.5%
5 284175
10.3%
0 278494
10.1%
9 272434
9.9%
4 257200
9.3%
6 249631
9.1%
7 228820
8.3%
8 216725
7.9%
Latin
ValueCountFrequency (%)
b 287500
18.8%
e 276077
18.1%
d 274180
17.9%
f 240722
15.7%
c 232602
15.2%
a 218379
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4284320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 363206
 
8.5%
1 316234
 
7.4%
3 287941
 
6.7%
b 287500
 
6.7%
5 284175
 
6.6%
0 278494
 
6.5%
e 276077
 
6.4%
d 274180
 
6.4%
9 272434
 
6.4%
4 257200
 
6.0%
Other values (6) 1386879
32.4%
Distinct22
Distinct (%)< 0.1%
Missing729736
Missing (%)89.0%
Memory size12.5 MiB
2023-07-30T15:15:14.894457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length151
Median length102
Mean length73.89952813
Min length1

Characters and Unicode

Total characters6640316
Distinct characters66
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
2nd rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
3rd rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
4th rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
5th rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
ValueCountFrequency (%)
mozilla/5.0 84660
12.7%
gecko/20100101 84639
12.7%
linux 44084
 
6.6%
x11 44062
 
6.6%
x86_64 44042
 
6.6%
rv:43.0 44032
 
6.6%
firefox/43.0 44032
 
6.6%
iceweasel/43.0.4 44032
 
6.6%
nt 40601
 
6.1%
6.1 40601
 
6.1%
Other values (64) 152441
22.8%
2023-07-30T15:15:15.541010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 640752
 
9.6%
577370
 
8.7%
. 403232
 
6.1%
1 395017
 
5.9%
e 315236
 
4.7%
/ 310396
 
4.7%
o 302897
 
4.6%
i 263721
 
4.0%
4 220222
 
3.3%
l 217528
 
3.3%
Other values (56) 2993945
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2444817
36.8%
Decimal Number 1913420
28.8%
Other Punctuation 935276
 
14.1%
Space Separator 577370
 
8.7%
Uppercase Letter 555943
 
8.4%
Open Punctuation 84707
 
1.3%
Close Punctuation 84707
 
1.3%
Connector Punctuation 44042
 
0.7%
Dash Punctuation 34
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 315236
12.9%
o 302897
12.4%
i 263721
10.8%
l 217528
8.9%
r 178234
 
7.3%
x 176827
 
7.2%
c 132853
 
5.4%
a 132851
 
5.4%
n 98352
 
4.0%
s 90090
 
3.7%
Other values (15) 536228
21.9%
Uppercase Letter
ValueCountFrequency (%)
M 84846
15.3%
G 84659
15.2%
F 84641
15.2%
L 48183
8.7%
I 44367
8.0%
X 44062
7.9%
W 41268
7.4%
T 40659
7.3%
N 40636
7.3%
P 20458
 
3.7%
Other values (11) 22164
 
4.0%
Decimal Number
ValueCountFrequency (%)
0 640752
33.5%
1 395017
20.6%
4 220222
 
11.5%
3 209470
 
10.9%
5 165927
 
8.7%
6 141023
 
7.4%
2 96828
 
5.1%
8 44086
 
2.3%
7 65
 
< 0.1%
9 30
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 403232
43.1%
/ 310396
33.2%
; 128799
 
13.8%
: 84639
 
9.0%
, 8210
 
0.9%
Space Separator
ValueCountFrequency (%)
577370
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84707
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84707
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 44042
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3639556
54.8%
Latin 3000760
45.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 315236
 
10.5%
o 302897
 
10.1%
i 263721
 
8.8%
l 217528
 
7.2%
r 178234
 
5.9%
x 176827
 
5.9%
c 132853
 
4.4%
a 132851
 
4.4%
n 98352
 
3.3%
s 90090
 
3.0%
Other values (36) 1092171
36.4%
Common
ValueCountFrequency (%)
0 640752
17.6%
577370
15.9%
. 403232
11.1%
1 395017
10.9%
/ 310396
8.5%
4 220222
 
6.1%
3 209470
 
5.8%
5 165927
 
4.6%
6 141023
 
3.9%
; 128799
 
3.5%
Other values (10) 447348
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6640316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 640752
 
9.6%
577370
 
8.7%
. 403232
 
6.1%
1 395017
 
5.9%
e 315236
 
4.7%
/ 310396
 
4.7%
o 302897
 
4.6%
i 263721
 
4.0%
4 220222
 
3.3%
l 217528
 
3.3%
Other values (56) 2993945
45.1%
Distinct77
Distinct (%)0.1%
Missing737454
Missing (%)90.0%
Memory size12.5 MiB
2023-07-30T15:15:15.885890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length33
Median length26
Mean length14.23717402
Min length1

Characters and Unicode

Total characters1169413
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowapplication/ocsp-response
2nd rowtext/html
3rd rowtext/css
4th rowtext/css
5th rowtext/css
ValueCountFrequency (%)
text/html 11650
14.2%
image/gif 11466
14.0%
application/javascript 8488
10.4%
application/ocsp-response 8437
10.3%
image/jpeg 7843
9.6%
text/javascript 7432
9.1%
application/x-javascript 6015
7.3%
text/css 4170
 
5.1%
application/json 4012
 
4.9%
text/xml 3982
 
4.9%
Other values (58) 8469
10.3%
2023-07-30T15:15:16.552793image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 126420
10.8%
t 124626
10.7%
i 115724
 
9.9%
p 108913
 
9.3%
/ 81968
 
7.0%
e 78761
 
6.7%
c 63501
 
5.4%
s 60649
 
5.2%
o 52725
 
4.5%
n 48254
 
4.1%
Other values (40) 307872
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1069384
91.4%
Other Punctuation 82294
 
7.0%
Dash Punctuation 16087
 
1.4%
Decimal Number 861
 
0.1%
Math Symbol 319
 
< 0.1%
Uppercase Letter 282
 
< 0.1%
Space Separator 186
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 126420
11.8%
t 124626
11.7%
i 115724
10.8%
p 108913
10.2%
e 78761
 
7.4%
c 63501
 
5.9%
s 60649
 
5.7%
o 52725
 
4.9%
n 48254
 
4.5%
l 46979
 
4.4%
Other values (15) 242832
22.7%
Uppercase Letter
ValueCountFrequency (%)
P 46
16.3%
G 42
14.9%
J 38
13.5%
E 38
13.5%
T 28
9.9%
M 20
7.1%
L 20
7.1%
H 14
 
5.0%
U 12
 
4.3%
F 8
 
2.8%
Other values (4) 16
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/ 81968
99.6%
. 294
 
0.4%
* 22
 
< 0.1%
, 10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 805
93.5%
4 50
 
5.8%
8 6
 
0.7%
Math Symbol
ValueCountFrequency (%)
+ 313
98.1%
= 6
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 16087
100.0%
Space Separator
ValueCountFrequency (%)
186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1069666
91.5%
Common 99747
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 126420
11.8%
t 124626
11.7%
i 115724
10.8%
p 108913
10.2%
e 78761
 
7.4%
c 63501
 
5.9%
s 60649
 
5.7%
o 52725
 
4.9%
n 48254
 
4.5%
l 46979
 
4.4%
Other values (29) 243114
22.7%
Common
ValueCountFrequency (%)
/ 81968
82.2%
- 16087
 
16.1%
2 805
 
0.8%
+ 313
 
0.3%
. 294
 
0.3%
186
 
0.2%
4 50
 
0.1%
* 22
 
< 0.1%
, 10
 
< 0.1%
= 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 126420
10.8%
t 124626
10.7%
i 115724
 
9.9%
p 108913
 
9.3%
/ 81968
 
7.0%
e 78761
 
6.7%
c 63501
 
5.4%
s 60649
 
5.2%
o 52725
 
4.5%
n 48254
 
4.1%
Other values (40) 307872
26.3%

label
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5063751232
Minimum0
Maximum1
Zeros404571
Zeros (%)49.4%
Negative0
Negative (%)0.0%
Memory size12.5 MiB
2023-07-30T15:15:16.788392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4999596612
Coefficient of variation (CV)0.9873306136
Kurtosis-1.999354496
Mean0.5063751232
Median Absolute Deviation (MAD)0
Skewness-0.02550261265
Sum415021
Variance0.2499596628
MonotonicityDecreasing
2023-07-30T15:15:16.976306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 415021
50.6%
0 404571
49.4%
ValueCountFrequency (%)
0 404571
49.4%
1 415021
50.6%
ValueCountFrequency (%)
1 415021
50.6%
0 404571
49.4%